Let me take a another stab at this. Recapping the original steps:
1. pto_gen -o output.pto 1.jpg 2.jpg 3.jpg 4.jpg 5.jpg 6.jpg 7.jpg 8.jpg 9.jpg 10.jpg 11.jpg 12.jpg 2. hugin_executor --assistant ./output.pto 3. hugin_executor --stitching --prefix=prefix ./output.pto Problems: 1) Attached Default.txt which captures the log output of the above steps. >From Line 112 to Line 143 we could see the match is made among the combinations of the images ex: image 0.jpg (its actually 1.jpg but zero indexed internally ) with all other images, likewise other images are matched as well. Ideally I want the match to be restricted to the sequence provided in the command line ie. 1 <> 2, 2<> 3 so on and so forth till 11 <> 12. Probable fix : During Step2 run the cpfind with a --linearmatch. In order to do that I had to use a user-defined-assistant fileas below. hugin_executor --assistant --user-defined-assistant=C:/Users/svrvs/Downloads/Feb24/general.assistant ./gen.pto Attached gen.log, general.assistant ( in this I don't think checkpto, cpclean are really needed but that's a experiment for another day ). This seem to take in the image as is per command line passed in step1. 2) Initially step2 was around a minute. step3 probably around 10 - 15 seconds. With the cpfind --linearmatch as in problem#1 the time was cut down to 23 seconds during step2, step3 not a drastic change. Btw, the images have restrictions to share On Friday, March 29, 2024 at 3:04:35 AM UTC-7 T. Modes wrote: > Venkat schrieb am Freitag, 29. März 2024 um 02:09:38 UTC+1: > > So when hugin_executor gets called with --assistant it calls > "cpfind" with some defaults. This results in trying all matches ( > regardless of sort or not > during the "pto_gen" step). > > > Either you have not set the multirow switch for the default cp generator > or something else is going wrong. > But have been said already and I have the feeling we are going in circles. > The best would be you provide a link to one image set and the log of > commands. Then we can try ourself and compare with your output. > > -- A list of frequently asked questions is available at: http://wiki.panotools.org/Hugin_FAQ --- You received this message because you are subscribed to the Google Groups "hugin and other free panoramic software" group. To unsubscribe from this group and stop receiving emails from it, send an email to [email protected]. To view this discussion on the web visit https://groups.google.com/d/msgid/hugin-ptx/1035433e-2ed0-4e8c-ba62-699977e913f9n%40googlegroups.com.
general.assistant
Description: Binary data
C:\Users\svrvs\Downloads\Feb24>hugin_executor --assistant
--user-defined-assistant=C:/Users/svrvs/Downloads/Feb24/general.assistant
./gen.pto
Searching control points
Hugin's cpfind 2022.0.0.9bb147ae7161 built by Thomas
based on Pan-o-matic by Anael Orlinski
Input file : ./gen.pto
Output file : ./gen.pto
Number of threads : 8
Input image options
Downscale to half-size : yes
Sieve 1 Options
Width : 10
Height : 10
Size : 100
==> Maximum keypoints per image : 10000
KDTree Options
Search steps : 200
Second match distance : 0.25
Matching Options
Mode : Linear match with length of 1 image
Distance threshold : 50
RANSAC Options
Mode : auto
Iterations : 1000
Distance threshold : 50
Minimum matches per image pair: 6
Sieve 2 Options
Width : 5
Height : 5
Size : 1
==> Maximum matches per image pair : 25
Project contains the following images:
Image 0
Imagefile: 1.jpg
Remapped : yes
Image 1
Imagefile: 2.jpg
Remapped : yes
Image 2
Imagefile: 3.jpg
Remapped : yes
Image 3
Imagefile: 4.jpg
Remapped : yes
Image 4
Imagefile: 5.jpg
Remapped : yes
Image 5
Imagefile: 6.jpg
Remapped : yes
Image 6
Imagefile: 7.jpg
Remapped : yes
Image 7
Imagefile: 8.jpg
Remapped : yes
Image 8
Imagefile: 9.jpg
Remapped : yes
Image 9
Imagefile: 10.jpg
Remapped : yes
Image 10
Imagefile: 11.jpg
Remapped : yes
Image 11
Imagefile: 12.jpg
Remapped : yes
--- Analyze Images ---
i0 : Load image...
i1 : Load image...
i2 : Load image...
i3 : Load image...
i4 : Load image...
i5 : Load image...
i6 : Load image...
i7 : Load image...
i3 : Remapping image...
i0 : Remapping image...
i2 : Remapping image...
i1 : Remapping image...
i4 : Remapping image...
i7 : Remapping image...
i5 : Remapping image...
i6 : Remapping image...
i2 : Convert to greyscale double...
i5 : Convert to greyscale double...
i6 : Convert to greyscale double...
i3 : Convert to greyscale double...
i1 : Convert to greyscale double...
i4 : Convert to greyscale double...
i0 : Convert to greyscale double...
i7 : Convert to greyscale double...
i2 : Build integral image...
i6 : Build integral image...
i3 : Build integral image...
i1 : Build integral image...
i4 : Build integral image...
i5 : Build integral image...
i0 : Build integral image...
i7 : Build integral image...
i2 : Build distance map...
i6 : Build distance map...
i3 : Build distance map...
i4 : Build distance map...
i5 : Build distance map...
i1 : Build distance map...
i0 : Build distance map...
i7 : Build distance map...
i2 : Find keypoints...
i6 : Find keypoints...
i3 : Find keypoints...
i4 : Find keypoints...
i1 : Find keypoints...
i5 : Find keypoints...
i7 : Find keypoints...
i0 : Find keypoints...
i2 : Found 58826 interest points.
i2 : Filtering keypoints...
i2 : Kept 9002 interest points.
i2 : Make keypoint descriptors...
i6 : Found 75342 interest points.
i6 : Filtering keypoints...
i6 : Kept 9227 interest points.
i6 : Make keypoint descriptors...
i3 : Found 60647 interest points.
i3 : Filtering keypoints...
i3 : Kept 9107 interest points.
i3 : Make keypoint descriptors...
i4 : Found 56525 interest points.
i4 : Filtering keypoints...
i1 : Found 55375 interest points.
i1 : Filtering keypoints...
i7 : Found 62444 interest points.
i7 : Filtering keypoints...
i0 : Found 46884 interest points.
i0 : Filtering keypoints...
i5 : Found 56952 interest points.
i5 : Filtering keypoints...
i4 : Kept 8929 interest points.
i4 : Make keypoint descriptors...
i1 : Kept 9015 interest points.
i0 : Kept 8205 interest points.
i1 : Make keypoint descriptors...
i0 : Make keypoint descriptors...
i5 : Kept 8986 interest points.
i7 : Kept 8906 interest points.
i5 : Make keypoint descriptors...
i7 : Make keypoint descriptors...
i2 : Remapping back keypoints...
i2 : Build KDTree...
i6 : Remapping back keypoints...
i6 : Build KDTree...
i3 : Remapping back keypoints...
i3 : Build KDTree...
i2 : Freeing memory...
i8 : Load image...
i0 : Remapping back keypoints...
i6 : Freeing memory...
i0 : Build KDTree...
i3 : Freeing memory...
i4 : Remapping back keypoints...
i8 : Remapping image...
i4 : Build KDTree...
i7 : Remapping back keypoints...
i1 : Remapping back keypoints...
i9 : Load image...
i7 : Build KDTree...
i1 : Build KDTree...
i5 : Remapping back keypoints...
i5 : Build KDTree...
i0 : Freeing memory...
i4 : Freeing memory...
i9 : Remapping image...
i7 : Freeing memory...
i1 : Freeing memory...
i5 : Freeing memory...
i10 : Load image...
i11 : Load image...
i10 : Remapping image...
i11 : Remapping image...
i8 : Convert to greyscale double...
i8 : Build integral image...
i8 : Build distance map...
i8 : Find keypoints...
i9 : Convert to greyscale double...
i9 : Build integral image...
i9 : Build distance map...
i11 : Convert to greyscale double...
i11 : Build integral image...
i10 : Convert to greyscale double...
i10 : Build integral image...
i11 : Build distance map...
i9 : Find keypoints...
i10 : Build distance map...
i11 : Find keypoints...
i10 : Find keypoints...
i8 : Found 65857 interest points.
i8 : Filtering keypoints...
i8 : Kept 9147 interest points.
i8 : Make keypoint descriptors...
i8 : Remapping back keypoints...
i8 : Build KDTree...
i8 : Freeing memory...
i9 : Found 81829 interest points.
i9 : Filtering keypoints...
i9 : Kept 9242 interest points.
i9 : Make keypoint descriptors...
i11 : Found 74266 interest points.
i11 : Filtering keypoints...
i11 : Kept 9199 interest points.
i10 : Found 73444 interest points.
i10 : Filtering keypoints...
i11 : Make keypoint descriptors...
i9 : Remapping back keypoints...
i9 : Build KDTree...
i10 : Kept 9153 interest points.
i10 : Make keypoint descriptors...
i9 : Freeing memory...
i11 : Remapping back keypoints...
i11 : Build KDTree...
i10 : Remapping back keypoints...
i10 : Build KDTree...
i11 : Freeing memory...
i10 : Freeing memory...
--- Find pair-wise matches ---
i1 <> i2 : Find Matches...
i2 <> i3 : Find Matches...
i3 <> i4 : Find Matches...
i4 <> i5 : Find Matches...
i5 <> i6 : Find Matches...
i6 <> i7 : Find Matches...
i7 <> i8 : Find Matches...
i0 <> i1 : Find Matches...
i0 <> i1 : Found 29 matches.
i0 <> i1 : RANSAC Filtering with Panorama model...
i0 <> i1 : Removed 12 matches. 17 remaining.
i0 <> i1 : Clustering matches...
i0 <> i1 : Kept 6 matches.
i8 <> i9 : Find Matches...
i2 <> i3 : Found 117 matches.
i2 <> i3 : RANSAC Filtering with Panorama model...
i1 <> i2 : Found 213 matches.
i1 <> i2 : RANSAC Filtering with Panorama model...
i3 <> i4 : Found 88 matches.
i3 <> i4 : RANSAC Filtering with Panorama model...
i4 <> i5 : Found 112 matches.
i4 <> i5 : RANSAC Filtering with Panorama model...
i5 <> i6 : Found 81 matches.
i5 <> i6 : RANSAC Filtering with Panorama model...
i7 <> i8 : Found 84 matches.
i7 <> i8 : RANSAC Filtering with Panorama model...
i2 <> i3 : Removed 23 matches. 94 remaining.
i2 <> i3 : Clustering matches...
i2 <> i3 : Kept 18 matches.
i9 <> i10 : Find Matches...
i6 <> i7 : Found 84 matches.
i6 <> i7 : RANSAC Filtering with Panorama model...
i1 <> i2 : Removed 10 matches. 203 remaining.
i1 <> i2 : Clustering matches...
i1 <> i2 : Kept 20 matches.
i10 <> i11 : Find Matches...
i3 <> i4 : Removed 34 matches. 54 remaining.
i3 <> i4 : Clustering matches...
i3 <> i4 : Kept 15 matches.
i4 <> i5 : Removed 28 matches. 84 remaining.
i4 <> i5 : Clustering matches...
i4 <> i5 : Kept 15 matches.
i5 <> i6 : Removed 21 matches. 60 remaining.
i5 <> i6 : Clustering matches...
i5 <> i6 : Kept 10 matches.
i7 <> i8 : Removed 29 matches. 55 remaining.
i7 <> i8 : Clustering matches...
i7 <> i8 : Kept 9 matches.
i6 <> i7 : Removed 5 matches. 79 remaining.
i6 <> i7 : Clustering matches...
i6 <> i7 : Kept 16 matches.
i8 <> i9 : Found 142 matches.
i8 <> i9 : RANSAC Filtering with Panorama model...
i9 <> i10 : Found 79 matches.
i9 <> i10 : RANSAC Filtering with Panorama model...
i8 <> i9 : Removed 45 matches. 97 remaining.
i8 <> i9 : Clustering matches...
i8 <> i9 : Kept 17 matches.
i10 <> i11 : Found 539 matches.
i10 <> i11 : RANSAC Filtering with Panorama model...
i9 <> i10 : Removed 25 matches. 54 remaining.
i9 <> i10 : Clustering matches...
i9 <> i10 : Kept 12 matches.
i10 <> i11 : Removed 28 matches. 511 remaining.
i10 <> i11 : Clustering matches...
i10 <> i11 : Kept 24 matches.
--- Write Project output ---
Written output to ./gen.pto
Detection took 23.312 seconds.
Check result
Opened project ./gen.pto
Project contains
12 images
1 lenses
12 stacks
162 control points
Control points statistics
Mean error : 249.10
Standard deviation: 107.55
Minimum : 18.92
Maximum : 378.43
All images are connected.
Cleaning control points
Step 1: Do image pair control point checking...
Step 2: Do whole panorama control point checking...
Removed 8 control points in step 1
Removed 5 control points in step 2
Written output to ./gen.pto
Searching line cp
linefind.exe is searching for vertical lines
Working on image ./1.jpg
Working on image ./2.jpg
Working on image ./3.jpg
Working on image ./4.jpg
Working on image ./5.jpg
Working on image ./6.jpg
Working on image ./7.jpg
Working on image ./8.jpg
Working on image ./9.jpg
Working on image ./10.jpg
Working on image ./11.jpg
Working on image ./12.jpg
Found 41 vertical lines
Written output to ./gen.pto
Optimizing
*** Adaptive geometric optimisation
Optimizing Variables
Strategy 1
Average (rms) distance between Controlpoints
after 0 iteration(s): 303.024014756524 units
Strategy 1
Average (rms) distance between Controlpoints
after 1 iteration(s): 6.80641721839699 units
Strategy 1
Average (rms) distance between Controlpoints
after 2 iteration(s): 5.80989409308026 units
Strategy 1
Average (rms) distance between Controlpoints
after 3 iteration(s): 5.44834237118372 units
Strategy 1
Average (rms) distance between Controlpoints
after 4 iteration(s): 5.42234657847403 units
Strategy 1
Average (rms) distance between Controlpoints
after 5 iteration(s): 5.17888306922269 units
Strategy 1
Average (rms) distance between Controlpoints
after 6 iteration(s): 5.14383070801125 units
Strategy 1
Average (rms) distance between Controlpoints
after 7 iteration(s): 5.14383070801125 units
Optimizing Variables
Strategy 2
Average (rms) distance between Controlpoints
after 0 iteration(s): 5.14383632673626 units
Strategy 2
Average (rms) distance between Controlpoints
after 1 iteration(s): 5.1127648367487 units
Strategy 2
Average (rms) distance between Controlpoints
after 2 iteration(s): 5.1127644700861 units
Optimizing Variables
Strategy 1
Average (rms) distance between Controlpoints
after 0 iteration(s): 578.666309297405 units
Strategy 1
Average (rms) distance between Controlpoints
after 1 iteration(s): 11.5685507444686 units
Strategy 1
Average (rms) distance between Controlpoints
after 2 iteration(s): 7.80747826813963 units
Strategy 1
Average (rms) distance between Controlpoints
after 3 iteration(s): 6.94768327974023 units
Strategy 1
Average (rms) distance between Controlpoints
after 4 iteration(s): 6.25176540804138 units
Strategy 1
Average (rms) distance between Controlpoints
after 5 iteration(s): 5.44602228822928 units
Strategy 1
Average (rms) distance between Controlpoints
after 6 iteration(s): 5.42739567489976 units
Optimizing Variables
Strategy 2
Average (rms) distance between Controlpoints
after 0 iteration(s): 5.42741773831437 units
Strategy 2
Average (rms) distance between Controlpoints
after 1 iteration(s): 5.39597427523659 units
Strategy 2
Average (rms) distance between Controlpoints
after 2 iteration(s): 5.39595691237254 units
Strategy 2
Average (rms) distance between Controlpoints
after 3 iteration(s): 5.39595689814649 units
Optimizing Variables
Strategy 1
Average (rms) distance between Controlpoints
after 0 iteration(s): 900.288554132328 units
Strategy 1
Average (rms) distance between Controlpoints
after 1 iteration(s): 130.397125397381 units
Strategy 1
Average (rms) distance between Controlpoints
after 2 iteration(s): 27.0805612495693 units
Strategy 1
Average (rms) distance between Controlpoints
after 3 iteration(s): 6.27801794924464 units
Strategy 1
Average (rms) distance between Controlpoints
after 4 iteration(s): 6.15180595236071 units
Strategy 1
Average (rms) distance between Controlpoints
after 5 iteration(s): 5.70670842413141 units
Strategy 1
Average (rms) distance between Controlpoints
after 6 iteration(s): 5.27373545072058 units
Strategy 1
Average (rms) distance between Controlpoints
after 7 iteration(s): 5.05634380891625 units
Strategy 1
Average (rms) distance between Controlpoints
after 8 iteration(s): 4.96029073663239 units
Strategy 1
Average (rms) distance between Controlpoints
after 9 iteration(s): 4.95154264428952 units
Optimizing Variables
Strategy 2
Average (rms) distance between Controlpoints
after 0 iteration(s): 4.95155274993351 units
Strategy 2
Average (rms) distance between Controlpoints
after 1 iteration(s): 4.94331213914469 units
Strategy 2
Average (rms) distance between Controlpoints
after 2 iteration(s): 4.94331047868049 units
Optimizing Variables
Strategy 1
Average (rms) distance between Controlpoints
after 0 iteration(s): 1114.38332806598 units
Strategy 1
Average (rms) distance between Controlpoints
after 1 iteration(s): 1021.8556048235 units
Strategy 1
Average (rms) distance between Controlpoints
after 2 iteration(s): 385.715598954134 units
Strategy 1
Average (rms) distance between Controlpoints
after 3 iteration(s): 135.155913335163 units
Strategy 1
Average (rms) distance between Controlpoints
after 4 iteration(s): 20.23525812034 units
Strategy 1
Average (rms) distance between Controlpoints
after 5 iteration(s): 10.6232550840548 units
Strategy 1
Average (rms) distance between Controlpoints
after 6 iteration(s): 8.27020894583494 units
Strategy 1
Average (rms) distance between Controlpoints
after 7 iteration(s): 7.96835145218071 units
Strategy 1
Average (rms) distance between Controlpoints
after 8 iteration(s): 7.96835145218071 units
Optimizing Variables
Strategy 2
Average (rms) distance between Controlpoints
after 0 iteration(s): 7.96838692715837 units
Strategy 2
Average (rms) distance between Controlpoints
after 1 iteration(s): 7.93831494930791 units
Strategy 2
Average (rms) distance between Controlpoints
after 2 iteration(s): 7.93831414955078 units
Optimizing Variables
Strategy 1
Average (rms) distance between Controlpoints
after 0 iteration(s): 1107.3250921387 units
Strategy 1
Average (rms) distance between Controlpoints
after 1 iteration(s): 539.593744219825 units
Strategy 1
Average (rms) distance between Controlpoints
after 2 iteration(s): 223.702452627402 units
Strategy 1
Average (rms) distance between Controlpoints
after 3 iteration(s): 37.1139528203032 units
Strategy 1
Average (rms) distance between Controlpoints
after 4 iteration(s): 30.8167987201998 units
Strategy 1
Average (rms) distance between Controlpoints
after 5 iteration(s): 10.4673967334943 units
Strategy 1
Average (rms) distance between Controlpoints
after 6 iteration(s): 7.33941310722795 units
Strategy 1
Average (rms) distance between Controlpoints
after 7 iteration(s): 7.16799904376436 units
Strategy 1
Average (rms) distance between Controlpoints
after 8 iteration(s): 7.15097852882301 units
Optimizing Variables
Strategy 2
Average (rms) distance between Controlpoints
after 0 iteration(s): 7.1510087021937 units
Strategy 2
Average (rms) distance between Controlpoints
after 1 iteration(s): 7.1490576516633 units
Strategy 2
Average (rms) distance between Controlpoints
after 2 iteration(s): 7.14905744915107 units
Optimizing Variables
Strategy 1
Average (rms) distance between Controlpoints
after 0 iteration(s): 963.206926280858 units
Strategy 1
Average (rms) distance between Controlpoints
after 1 iteration(s): 255.102765739175 units
Strategy 1
Average (rms) distance between Controlpoints
after 2 iteration(s): 35.8200673371214 units
Strategy 1
Average (rms) distance between Controlpoints
after 3 iteration(s): 27.0970430537545 units
Strategy 1
Average (rms) distance between Controlpoints
after 4 iteration(s): 11.3609775645847 units
Strategy 1
Average (rms) distance between Controlpoints
after 5 iteration(s): 11.2827057194359 units
Strategy 1
Average (rms) distance between Controlpoints
after 6 iteration(s): 8.67195506239925 units
Strategy 1
Average (rms) distance between Controlpoints
after 7 iteration(s): 8.31951431528621 units
Strategy 1
Average (rms) distance between Controlpoints
after 8 iteration(s): 8.21791584793037 units
Optimizing Variables
Strategy 2
Average (rms) distance between Controlpoints
after 0 iteration(s): 8.21797604154698 units
Strategy 2
Average (rms) distance between Controlpoints
after 1 iteration(s): 8.20413932257283 units
Strategy 2
Average (rms) distance between Controlpoints
after 2 iteration(s): 8.20412360494715 units
Strategy 2
Average (rms) distance between Controlpoints
after 3 iteration(s): 8.20412357604636 units
Optimizing Variables
Strategy 1
Average (rms) distance between Controlpoints
after 0 iteration(s): 708.821976537426 units
Strategy 1
Average (rms) distance between Controlpoints
after 1 iteration(s): 72.8151686017507 units
Strategy 1
Average (rms) distance between Controlpoints
after 2 iteration(s): 21.8309892090477 units
Strategy 1
Average (rms) distance between Controlpoints
after 3 iteration(s): 17.7898865710044 units
Strategy 1
Average (rms) distance between Controlpoints
after 4 iteration(s): 14.969412422614 units
Strategy 1
Average (rms) distance between Controlpoints
after 5 iteration(s): 3.3867842008419 units
Strategy 1
Average (rms) distance between Controlpoints
after 6 iteration(s): 3.32811879569253 units
Strategy 1
Average (rms) distance between Controlpoints
after 7 iteration(s): 3.25191474909218 units
Strategy 1
Average (rms) distance between Controlpoints
after 8 iteration(s): 2.97993346109237 units
Strategy 1
Average (rms) distance between Controlpoints
after 9 iteration(s): 2.96083826903348 units
Optimizing Variables
Strategy 2
Average (rms) distance between Controlpoints
after 0 iteration(s): 2.96084052569509 units
Strategy 2
Average (rms) distance between Controlpoints
after 1 iteration(s): 2.96010059245627 units
Strategy 2
Average (rms) distance between Controlpoints
after 2 iteration(s): 2.96010057239197 units
Optimizing Variables
Strategy 1
Average (rms) distance between Controlpoints
after 0 iteration(s): 399.071829649182 units
Strategy 1
Average (rms) distance between Controlpoints
after 1 iteration(s): 55.5487239263167 units
Strategy 1
Average (rms) distance between Controlpoints
after 2 iteration(s): 33.442477905568 units
Strategy 1
Average (rms) distance between Controlpoints
after 3 iteration(s): 33.2824486672404 units
Strategy 1
Average (rms) distance between Controlpoints
after 4 iteration(s): 23.9693114313561 units
Strategy 1
Average (rms) distance between Controlpoints
after 5 iteration(s): 23.7162638466375 units
Strategy 1
Average (rms) distance between Controlpoints
after 6 iteration(s): 17.2900449111871 units
Strategy 1
Average (rms) distance between Controlpoints
after 7 iteration(s): 9.49287975353646 units
Strategy 1
Average (rms) distance between Controlpoints
after 8 iteration(s): 8.69468015561569 units
Strategy 1
Average (rms) distance between Controlpoints
after 9 iteration(s): 8.35190707238096 units
Strategy 1
Average (rms) distance between Controlpoints
after 10 iteration(s): 8.27796898140855 units
Optimizing Variables
Strategy 2
Average (rms) distance between Controlpoints
after 0 iteration(s): 8.27800505673213 units
Strategy 2
Average (rms) distance between Controlpoints
after 1 iteration(s): 8.27246894372105 units
Strategy 2
Average (rms) distance between Controlpoints
after 2 iteration(s): 8.27245255463714 units
Strategy 2
Average (rms) distance between Controlpoints
after 3 iteration(s): 8.27245249199163 units
Optimizing Variables
Strategy 1
Average (rms) distance between Controlpoints
after 0 iteration(s): 116.672755782664 units
Strategy 1
Average (rms) distance between Controlpoints
after 1 iteration(s): 10.4749778094117 units
Strategy 1
Average (rms) distance between Controlpoints
after 2 iteration(s): 7.27339681370408 units
Strategy 1
Average (rms) distance between Controlpoints
after 3 iteration(s): 6.86964643694749 units
Strategy 1
Average (rms) distance between Controlpoints
after 4 iteration(s): 6.70370723580583 units
Strategy 1
Average (rms) distance between Controlpoints
after 5 iteration(s): 6.70370723580583 units
Optimizing Variables
Strategy 2
Average (rms) distance between Controlpoints
after 0 iteration(s): 6.70372636527466 units
Strategy 2
Average (rms) distance between Controlpoints
after 1 iteration(s): 6.68345800837019 units
Strategy 2
Average (rms) distance between Controlpoints
after 2 iteration(s): 6.68345702974276 units
Optimizing Variables
Strategy 1
Average (rms) distance between Controlpoints
after 0 iteration(s): 144.04745989919 units
Strategy 1
Average (rms) distance between Controlpoints
after 1 iteration(s): 34.2451257195411 units
Strategy 1
Average (rms) distance between Controlpoints
after 2 iteration(s): 22.5201431653815 units
Strategy 1
Average (rms) distance between Controlpoints
after 3 iteration(s): 16.0673531318546 units
Strategy 1
Average (rms) distance between Controlpoints
after 4 iteration(s): 14.965995090342 units
Strategy 1
Average (rms) distance between Controlpoints
after 5 iteration(s): 8.29322598210024 units
Strategy 1
Average (rms) distance between Controlpoints
after 6 iteration(s): 7.22889785903389 units
Strategy 1
Average (rms) distance between Controlpoints
after 7 iteration(s): 7.13239682936084 units
Strategy 1
Average (rms) distance between Controlpoints
after 8 iteration(s): 7.13239682936084 units
Optimizing Variables
Strategy 2
Average (rms) distance between Controlpoints
after 0 iteration(s): 7.13242598915944 units
Strategy 2
Average (rms) distance between Controlpoints
after 1 iteration(s): 7.12417473224486 units
Strategy 2
Average (rms) distance between Controlpoints
after 2 iteration(s): 7.12417009248585 units
Strategy 2
Average (rms) distance between Controlpoints
after 3 iteration(s): 7.12417008723715 units
Optimizing Variables
Strategy 1
Average (rms) distance between Controlpoints
after 0 iteration(s): 109.690710568123 units
Strategy 1
Average (rms) distance between Controlpoints
after 1 iteration(s): 3.48403027025569 units
Strategy 1
Average (rms) distance between Controlpoints
after 2 iteration(s): 1.89542670733887 units
Strategy 1
Average (rms) distance between Controlpoints
after 3 iteration(s): 1.68232438848049 units
Strategy 1
Average (rms) distance between Controlpoints
after 4 iteration(s): 1.68232438848049 units
Optimizing Variables
Strategy 2
Average (rms) distance between Controlpoints
after 0 iteration(s): 1.68232547705269 units
Strategy 2
Average (rms) distance between Controlpoints
after 1 iteration(s): 1.6652908687613 units
Strategy 2
Average (rms) distance between Controlpoints
after 2 iteration(s): 1.66529063112584 units
Optimizing Variables
Strategy 1
Average (rms) distance between Controlpoints
after 0 iteration(s): 8.78153853935514 units
Strategy 1
Average (rms) distance between Controlpoints
after 1 iteration(s): 5.66024702546209 units
Strategy 1
Average (rms) distance between Controlpoints
after 2 iteration(s): 5.64891842485552 units
Strategy 1
Average (rms) distance between Controlpoints
after 3 iteration(s): 5.59395325475873 units
Strategy 1
Average (rms) distance between Controlpoints
after 4 iteration(s): 5.59395325475873 units
Optimizing Variables
Strategy 2
Average (rms) distance between Controlpoints
after 0 iteration(s): 5.59397769711978 units
Strategy 2
Average (rms) distance between Controlpoints
after 1 iteration(s): 5.55729910180488 units
Strategy 2
Average (rms) distance between Controlpoints
after 2 iteration(s): 5.55726869022815 units
Strategy 2
Average (rms) distance between Controlpoints
after 3 iteration(s): 5.55726862257925 units
Optimizing Variables
Strategy 1
Average (rms) distance between Controlpoints
after 0 iteration(s): 5.55733700692781 units
Strategy 1
Average (rms) distance between Controlpoints
after 1 iteration(s): 2.42770945837954 units
Strategy 1
Average (rms) distance between Controlpoints
after 2 iteration(s): 2.34024984299438 units
Strategy 1
Average (rms) distance between Controlpoints
after 3 iteration(s): 2.17529770299906 units
Strategy 1
Average (rms) distance between Controlpoints
after 4 iteration(s): 2.09445135326048 units
Strategy 1
Average (rms) distance between Controlpoints
after 5 iteration(s): 1.82186992386225 units
Strategy 1
Average (rms) distance between Controlpoints
after 6 iteration(s): 1.77240073721759 units
Strategy 1
Average (rms) distance between Controlpoints
after 7 iteration(s): 1.77017712078579 units
Optimizing Variables
Strategy 2
Average (rms) distance between Controlpoints
after 0 iteration(s): 1.770177604005 units
Strategy 2
Average (rms) distance between Controlpoints
after 1 iteration(s): 1.74786246158963 units
Strategy 2
Average (rms) distance between Controlpoints
after 2 iteration(s): 1.74772245430216 units
Strategy 2
Average (rms) distance between Controlpoints
after 3 iteration(s): 1.74772240895693 units
Skipping automatic leveling because of existing vertical control points.
loading: ./5.jpg
downscaling: 2560x1440 1280x720 640x360
loading: ./1.jpg
downscaling: 2560x1440 1280x720 640x360
loading: ./6.jpg
downscaling: 2560x1440 1280x720 640x360
loading: ./8.jpg
downscaling: 2560x1440 1280x720 640x360
loading: ./4.jpg
downscaling: 2560x1440 1280x720 640x360
loading: ./3.jpg
downscaling: 2560x1440 1280x720 640x360
loading: ./2.jpg
downscaling: 2560x1440 1280x720 640x360
loading: ./7.jpg
downscaling: 2560x1440 1280x720 640x360
loading: ./10.jpg
downscaling: 2560x1440 1280x720 640x360
loading: ./9.jpg
downscaling: 2560x1440 1280x720 640x360
loading: ./12.jpg
downscaling: 2560x1440 1280x720 640x360
loading: ./11.jpg
downscaling: 2560x1440 1280x720 640x360
Sampling points
sampling points
extracting good points
Selected 2400 points
Photometric Optimization
Iteration: 0, error: 11.908922
Iteration: 1, error: 8.266354
Iteration: 2, error: 8.266354
Iteration: 3, error: 7.551198
Iteration: 4, error: 7.551198
Iteration: 5, error: 7.551198
Iteration: 6, error: 7.540148
Iteration: 7, error: 7.498032
Iteration: 8, error: 7.498032
Iteration: 9, error: 7.498032
Iteration: 10, error: 7.482000
Iteration: 11, error: 7.393282
Iteration: 12, error: 7.266028
Iteration: 13, error: 7.244353
Iteration: 14, error: 7.241464
Iteration: 15, error: 7.241464
Iteration: 16, error: 7.241464
Iteration: 17, error: 7.241063
Iteration: 18, error: 7.241063
Iteration: 19, error: 7.240602
Iteration: 20, error: 7.239920
Iteration: 21, error: 7.239803
Iteration: 22, error: 7.239803
Iteration: 23, error: 7.237941
Iteration: 24, error: 7.237885
Iteration: 25, error: 7.237885
Iteration: 26, error: 7.237861
Iteration: 27, error: 7.237861
Iteration: 28, error: 7.237861
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Iteration: 31, error: 7.237682
Iteration: 32, error: 7.237674
Iteration: 33, error: 7.237674
Iteration: 34, error: 7.237671
Iteration: 35, error: 7.237668
Iteration: 36, error: 7.237667
Iteration: 37, error: 7.237666
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Iteration: 42, error: 7.237664
Iteration: 43, error: 7.237643
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Iteration: 46, error: 7.237642
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Iteration: 100, error: 7.237642
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Iteration: 102, error: 7.237642
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Iteration: 109, error: 7.237642
Iteration: 110, error: 7.237642
Iteration: 0, error: 7.237642
Iteration: 1, error: 6.981382
Iteration: 2, error: 6.971551
Iteration: 3, error: 6.971551
Iteration: 4, error: 6.971551
Iteration: 5, error: 6.971551
Iteration: 6, error: 6.971551
Iteration: 7, error: 6.968818
Iteration: 8, error: 6.966991
Iteration: 9, error: 6.965964
Iteration: 10, error: 6.965509
Iteration: 11, error: 6.965242
Iteration: 12, error: 6.964992
Iteration: 13, error: 6.964884
Iteration: 14, error: 6.964864
Iteration: 15, error: 6.964861
Iteration: 16, error: 6.964861
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Iteration: 21, error: 6.964759
Iteration: 22, error: 6.964753
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Iteration: 26, error: 6.964753
Iteration: 27, error: 6.964753
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Iteration: 30, error: 6.964743
Iteration: 31, error: 6.964738
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Iteration: 33, error: 6.964737
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Iteration: 35, error: 6.964735
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Iteration: 55, error: 6.964733
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Iteration: 57, error: 6.964724
Iteration: 58, error: 6.964721
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Iteration: 0, error: 6.964717
Iteration: 1, error: 6.731304
Iteration: 2, error: 6.677770
Iteration: 3, error: 6.677770
Iteration: 4, error: 6.676172
Iteration: 5, error: 6.675425
Iteration: 6, error: 6.673225
Iteration: 7, error: 6.673225
Iteration: 8, error: 6.673225
Iteration: 9, error: 6.672051
Iteration: 10, error: 6.672051
Iteration: 11, error: 6.671955
Iteration: 12, error: 6.671955
Iteration: 13, error: 6.671887
Iteration: 14, error: 6.671887
Iteration: 15, error: 6.671705
Iteration: 16, error: 6.671588
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Iteration: 18, error: 6.669942
Iteration: 19, error: 6.668486
Iteration: 20, error: 6.667035
Iteration: 21, error: 6.666063
Iteration: 22, error: 6.665756
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Iteration: 25, error: 6.664326
Iteration: 26, error: 6.660557
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Iteration: 30, error: 6.648114
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Iteration: 48, error: 6.595273
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Iteration: 50, error: 6.593629
Iteration: 51, error: 6.593629
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Iteration: 53, error: 6.593316
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Iteration: 58, error: 6.589177
Iteration: 59, error: 6.588878
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Iteration: 65, error: 6.588676
Iteration: 66, error: 6.588590
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Iteration: 72, error: 6.588486
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Iteration: 137, error: 6.588381
Searching for best crop
Calculate optimal size of panorama
Setting canvas size to 4360 x 1381
Searching for best crop rectangle
Run called
Inner 256 3788840: 0 4360 - 256 1125
Starting 256: 0 4360 - 256 1125
Starting 128: 0 4360 - 256 1125
Starting 64: 0 4360 - 256 1253
Starting 32: 0 4360 - 192 1317
Starting 16: 0 4360 - 160 1349
Starting 8: 0 4360 - 144 1349
Starting 4: 0 4360 - 136 1357
Starting 2: 0 4360 - 136 1357
Starting 1: 0 4360 - 136 1357
Set crop size to 0,136,4360,1358
Written output to ./gen.pto
C:\Users\svrvs\Downloads\Feb24>
C:\Users\svrvs\Downloads\Feb24>
C:\Users\svrvs\Downloads\Feb24>
C:\Users\svrvs\Downloads\Feb24>hugin_executor --stitching --prefix=out_gen
./gen.pto
============================================
Stitching panorama...
============================================
Platform: Windows 10 (build 19045), 64-bit edition
Version: 2022.0.0.9bb147ae7161 built by Thomas
Working directory: C:\Users\svrvs\Downloads\Feb24
Output prefix: out_gen
Blender: enblend 4.3-8243911d8684
ExifTool version: 12.50
Number of active images: 12
Output exposure value: 7.9
Canvas size: 4360x1381
ROI: (0, 136) - (4360, 1358)
FOV: 360x114
Projection: Equirectangular(2)
Using GPU for remapping: false
Panorama Outputs:
* Exposure corrected, low dynamic range
First input image
Number: 0
Filename: C:\Users\svrvs\Downloads\Feb24\1.jpg
Size: 2560x1440
Projection: Normal (rectilinear)
Response type: custom (EMoR)
HFOV: 105
Exposure value: 8.2
Remapping LDR images...
Multiple images output
loading 1.jpg
remapping 1.jpg
saving out_gen0000.tif
loading 2.jpg
remapping 2.jpg
saving out_gen0001.tif
loading 3.jpg
remapping 3.jpg
saving out_gen0002.tif
loading 4.jpg
remapping 4.jpg
saving out_gen0003.tif
loading 5.jpg
remapping 5.jpg
saving out_gen0004.tif
loading 6.jpg
remapping 6.jpg
saving out_gen0005.tif
loading 7.jpg
remapping 7.jpg
saving out_gen0006.tif
loading 8.jpg
remapping 8.jpg
saving out_gen0007.tif
loading 9.jpg
remapping 9.jpg
saving out_gen0008.tif
loading 10.jpg
remapping 10.jpg
saving out_gen0009.tif
loading 11.jpg
remapping 11.jpg
saving out_gen0010.tif
loading 12.jpg
remapping 12.jpg
saving out_gen0011.tif
Blending images...
enblend: warning: some images are redundant and will not be blended
enblend: note: usually this means that at least one of the images
enblend: note: does not belong to the set
Updating metadata...
1 image files updated
Removing temporary files
Default execution:
Env - Windows 10
Processor Intel(R) Core(TM) i5-8250U CPU @ 1.60GHz, 1800 Mhz, 4 Core(s),
8 Logical Processor(s)
Total 3 steps:
1. pto_gen -o output.pto 1.jpg 2.jpg 3.jpg 4.jpg 5.jpg 6.jpg 7.jpg 8.jpg 9.jpg
10.jpg 11.jpg 12.jpg
2. hugin_executor --assistant ./output.pto
3. hugin_executor --stitching --prefix=prefix ./output.pto
======================================
Step 1
C:\Users\svrvs\Downloads\Feb24>pto_gen -o output.pto 1.jpg 2.jpg 3.jpg 4.jpg
5.jpg 6.jpg 7.jpg 8.jpg 9.jpg 10.jpg 11.jpg 12.jpg
Generating pto file...
Reading C:\Users\svrvs\Downloads\Feb24\1.jpg...
Reading C:\Users\svrvs\Downloads\Feb24\2.jpg...
Reading C:\Users\svrvs\Downloads\Feb24\3.jpg...
Reading C:\Users\svrvs\Downloads\Feb24\4.jpg...
Reading C:\Users\svrvs\Downloads\Feb24\5.jpg...
Reading C:\Users\svrvs\Downloads\Feb24\6.jpg...
Reading C:\Users\svrvs\Downloads\Feb24\7.jpg...
Reading C:\Users\svrvs\Downloads\Feb24\8.jpg...
Reading C:\Users\svrvs\Downloads\Feb24\9.jpg...
Reading C:\Users\svrvs\Downloads\Feb24\10.jpg...
Reading C:\Users\svrvs\Downloads\Feb24\11.jpg...
Reading C:\Users\svrvs\Downloads\Feb24\12.jpg...
Assigned 1 lenses.
Written output to C:\Users\svrvs\Downloads\Feb24\output.pto
C:\Users\svrvs\Downloads\Feb24>
==================================================================
Step2
C:\Users\svrvs\Downloads\Feb24>hugin_executor --assistant ./output.pto
Searching for control points...
Hugin's cpfind 2022.0.0.9bb147ae7161 built by Thomas
based on Pan-o-matic by Anael Orlinski
Project contains the following images:
Image 0
Imagefile: C:\Users\svrvs\Downloads\Feb24\1.jpg
Remapped : yes
Image 1
Imagefile: C:\Users\svrvs\Downloads\Feb24\2.jpg
Remapped : yes
Image 2
Imagefile: C:\Users\svrvs\Downloads\Feb24\3.jpg
Remapped : yes
Image 3
Imagefile: C:\Users\svrvs\Downloads\Feb24\4.jpg
Remapped : yes
Image 4
Imagefile: C:\Users\svrvs\Downloads\Feb24\5.jpg
Remapped : yes
Image 5
Imagefile: C:\Users\svrvs\Downloads\Feb24\6.jpg
Remapped : yes
Image 6
Imagefile: C:\Users\svrvs\Downloads\Feb24\7.jpg
Remapped : yes
Image 7
Imagefile: C:\Users\svrvs\Downloads\Feb24\8.jpg
Remapped : yes
Image 8
Imagefile: C:\Users\svrvs\Downloads\Feb24\9.jpg
Remapped : yes
Image 9
Imagefile: C:\Users\svrvs\Downloads\Feb24\10.jpg
Remapped : yes
Image 10
Imagefile: C:\Users\svrvs\Downloads\Feb24\11.jpg
Remapped : yes
Image 11
Imagefile: C:\Users\svrvs\Downloads\Feb24\12.jpg
Remapped : yes
--- Analyze Images ---
i0 : Analyzing image...
i1 : Analyzing image...
i2 : Analyzing image...
i3 : Analyzing image...
i4 : Analyzing image...
i5 : Analyzing image...
i6 : Analyzing image...
i7 : Analyzing image...
i8 : Analyzing image...
i9 : Analyzing image...
i10 : Analyzing image...
i11 : Analyzing image...
--- Find matches ---
i0 <> i1 : Found 6 matches
i2 <> i3 : Found 17 matches
i3 <> i4 : Found 12 matches
i5 <> i6 : Found 12 matches
i1 <> i2 : Found 19 matches
i4 <> i5 : Found 18 matches
i7 <> i8 : Found 12 matches
i6 <> i7 : Found 11 matches
i8 <> i9 : Found 15 matches
i9 <> i10 : Found 12 matches
i10 <> i11 : Found 24 matches
--- Find matches for overlapping images ---
i0 <> i3 : Found 0 matches
i0 <> i9 : Found 9 matches
i0 <> i8 : Found 0 matches
i0 <> i7 : Found 0 matches
i0 <> i2 : Found 0 matches
i0 <> i10 : Found 18 matches
i0 <> i11 : Found 18 matches
i1 <> i3 : Found 0 matches
i1 <> i10 : Found 0 matches
i1 <> i9 : Found 0 matches
i1 <> i8 : Found 0 matches
i1 <> i11 : Found 0 matches
i2 <> i9 : Found 0 matches
i2 <> i5 : Found 0 matches
i2 <> i4 : Found 0 matches
i2 <> i10 : Found 0 matches
i2 <> i11 : Found 0 matches
i3 <> i6 : Found 0 matches
i3 <> i10 : Found 0 matches
i3 <> i11 : Found 0 matches
i3 <> i5 : Found 4 matches
i4 <> i6 : Found 6 matches
i4 <> i7 : Found 0 matches
i5 <> i7 : Found 0 matches
i7 <> i9 : Found 0 matches
i6 <> i8 : Found 0 matches
i7 <> i11 : Found 0 matches
i7 <> i10 : Found 0 matches
i8 <> i10 : Found 0 matches
i9 <> i11 : Found 13 matches
i8 <> i11 : Found 0 matches
--- Write Project output ---
Written output to C:\Users\svrvs\AppData\Local\Temp\ap_77FC.tmp
Detection took 48.547 seconds.
Written output to ./output.pto
Statistically cleaning of control points...
Step 1: Do image pair control point checking...
Step 2: Do whole panorama control point checking...
Removed 8 control points in step 1
Removed 79 control points in step 2
Written output to ./output.pto
Searching for vertical lines...
linefind is searching for vertical lines
Working on image ./3.jpg
Working on image ./2.jpg
Working on image ./1.jpg
Working on image ./4.jpg
Working on image ./8.jpg
Working on image ./9.jpg
Working on image ./10.jpg
Working on image ./11.jpg
Working on image ./12.jpg
Found 34 vertical lines
Written output to ./output.pto
Opened project ./output.pto
Project contains
12 images
1 lenses
12 stacks
173 control points
Control points statistics
Mean error : 209.87
Standard deviation: 151.90
Minimum : 0.00
Maximum : 573.38
All images are connected.
Optimizing...
*** Adaptive geometric optimisation
Optimizing Variables
Strategy 1
Average (rms) distance between Controlpoints
after 0 iteration(s): 310.327309443578 units
Strategy 1
Average (rms) distance between Controlpoints
after 1 iteration(s): 305.610829276626 units
Strategy 1
Average (rms) distance between Controlpoints
after 2 iteration(s): 297.46842354766 units
Strategy 1
Average (rms) distance between Controlpoints
after 3 iteration(s): 282.903111798256 units
Strategy 1
Average (rms) distance between Controlpoints
after 4 iteration(s): 256.429959505264 units
Strategy 1
Average (rms) distance between Controlpoints
after 5 iteration(s): 217.199843746493 units
Strategy 1
Average (rms) distance between Controlpoints
after 6 iteration(s): 164.70983885213 units
Strategy 1
Average (rms) distance between Controlpoints
after 7 iteration(s): 79.4550770822552 units
Strategy 1
Average (rms) distance between Controlpoints
after 8 iteration(s): 38.151538958255 units
Strategy 1
Average (rms) distance between Controlpoints
after 9 iteration(s): 11.0580592273952 units
Strategy 1
Average (rms) distance between Controlpoints
after 10 iteration(s): 3.66950659621635 units
Strategy 1
Average (rms) distance between Controlpoints
after 11 iteration(s): 3.31476759867177 units
Strategy 1
Average (rms) distance between Controlpoints
after 12 iteration(s): 3.05561293764999 units
Strategy 1
Average (rms) distance between Controlpoints
after 13 iteration(s): 2.54803009382958 units
Strategy 1
Average (rms) distance between Controlpoints
after 14 iteration(s): 2.44814028569428 units
Strategy 1
Average (rms) distance between Controlpoints
after 15 iteration(s): 2.42458015540623 units
Optimizing Variables
Strategy 2
Average (rms) distance between Controlpoints
after 0 iteration(s): 2.42458061498759 units
Strategy 2
Average (rms) distance between Controlpoints
after 1 iteration(s): 2.40642702000142 units
Strategy 2
Average (rms) distance between Controlpoints
after 2 iteration(s): 2.40642536006603 units
Strategy 2
Average (rms) distance between Controlpoints
after 3 iteration(s): 2.40642535944165 units
Optimizing Variables
Strategy 1
Average (rms) distance between Controlpoints
after 0 iteration(s): 520.286897672253 units
Strategy 1
Average (rms) distance between Controlpoints
after 1 iteration(s): 35.1954503733153 units
Strategy 1
Average (rms) distance between Controlpoints
after 2 iteration(s): 16.397532509977 units
Strategy 1
Average (rms) distance between Controlpoints
after 3 iteration(s): 6.35667247242314 units
Strategy 1
Average (rms) distance between Controlpoints
after 4 iteration(s): 5.36081955890616 units
Strategy 1
Average (rms) distance between Controlpoints
after 5 iteration(s): 5.28510704399101 units
Optimizing Variables
Strategy 2
Average (rms) distance between Controlpoints
after 0 iteration(s): 5.28510771938776 units
Strategy 2
Average (rms) distance between Controlpoints
after 1 iteration(s): 5.27520062078784 units
Strategy 2
Average (rms) distance between Controlpoints
after 2 iteration(s): 5.27519648785118 units
Strategy 2
Average (rms) distance between Controlpoints
after 3 iteration(s): 5.27519648098425 units
Optimizing Variables
Strategy 1
Average (rms) distance between Controlpoints
after 0 iteration(s): 210.502833494564 units
Strategy 1
Average (rms) distance between Controlpoints
after 1 iteration(s): 6.90893011611339 units
Strategy 1
Average (rms) distance between Controlpoints
after 2 iteration(s): 6.58326816260651 units
Strategy 1
Average (rms) distance between Controlpoints
after 3 iteration(s): 6.44540202452023 units
Strategy 1
Average (rms) distance between Controlpoints
after 4 iteration(s): 6.44540202452023 units
Optimizing Variables
Strategy 2
Average (rms) distance between Controlpoints
after 0 iteration(s): 6.4454142947326 units
Strategy 2
Average (rms) distance between Controlpoints
after 1 iteration(s): 6.44191586804722 units
Strategy 2
Average (rms) distance between Controlpoints
after 2 iteration(s): 6.44191575744785 units
Optimizing Variables
Strategy 1
Average (rms) distance between Controlpoints
after 0 iteration(s): 204.041601398963 units
Strategy 1
Average (rms) distance between Controlpoints
after 1 iteration(s): 8.68894214878983 units
Strategy 1
Average (rms) distance between Controlpoints
after 2 iteration(s): 5.79331130482455 units
Strategy 1
Average (rms) distance between Controlpoints
after 3 iteration(s): 5.46956324717723 units
Strategy 1
Average (rms) distance between Controlpoints
after 4 iteration(s): 5.40440589861502 units
Strategy 1
Average (rms) distance between Controlpoints
after 5 iteration(s): 5.40440589861502 units
Optimizing Variables
Strategy 2
Average (rms) distance between Controlpoints
after 0 iteration(s): 5.40441635259134 units
Strategy 2
Average (rms) distance between Controlpoints
after 1 iteration(s): 5.38363811757467 units
Strategy 2
Average (rms) distance between Controlpoints
after 2 iteration(s): 5.38363756462706 units
Optimizing Variables
Strategy 1
Average (rms) distance between Controlpoints
after 0 iteration(s): 575.892103284133 units
Strategy 1
Average (rms) distance between Controlpoints
after 1 iteration(s): 24.0406460336845 units
Strategy 1
Average (rms) distance between Controlpoints
after 2 iteration(s): 15.1125764277738 units
Strategy 1
Average (rms) distance between Controlpoints
after 3 iteration(s): 5.02292520092365 units
Strategy 1
Average (rms) distance between Controlpoints
after 4 iteration(s): 4.76356335806174 units
Strategy 1
Average (rms) distance between Controlpoints
after 5 iteration(s): 4.76347510837964 units
Optimizing Variables
Strategy 2
Average (rms) distance between Controlpoints
after 0 iteration(s): 4.763489183733 units
Strategy 2
Average (rms) distance between Controlpoints
after 1 iteration(s): 4.76307412064454 units
Strategy 2
Average (rms) distance between Controlpoints
after 2 iteration(s): 4.76307404752697 units
Optimizing Variables
Strategy 1
Average (rms) distance between Controlpoints
after 0 iteration(s): 755.563184106581 units
Strategy 1
Average (rms) distance between Controlpoints
after 1 iteration(s): 49.1589590582456 units
Strategy 1
Average (rms) distance between Controlpoints
after 2 iteration(s): 9.09105734246453 units
Strategy 1
Average (rms) distance between Controlpoints
after 3 iteration(s): 8.00751528196074 units
Strategy 1
Average (rms) distance between Controlpoints
after 4 iteration(s): 7.4945857321543 units
Strategy 1
Average (rms) distance between Controlpoints
after 5 iteration(s): 7.37847779398586 units
Strategy 1
Average (rms) distance between Controlpoints
after 6 iteration(s): 7.37847779398586 units
Optimizing Variables
Strategy 2
Average (rms) distance between Controlpoints
after 0 iteration(s): 7.37849644692458 units
Strategy 2
Average (rms) distance between Controlpoints
after 1 iteration(s): 7.36542475101207 units
Strategy 2
Average (rms) distance between Controlpoints
after 2 iteration(s): 7.36542034463683 units
Strategy 2
Average (rms) distance between Controlpoints
after 3 iteration(s): 7.36542033776783 units
Optimizing Variables
Strategy 1
Average (rms) distance between Controlpoints
after 0 iteration(s): 939.172560792033 units
Strategy 1
Average (rms) distance between Controlpoints
after 1 iteration(s): 46.8594971816717 units
Strategy 1
Average (rms) distance between Controlpoints
after 2 iteration(s): 35.890611307807 units
Strategy 1
Average (rms) distance between Controlpoints
after 3 iteration(s): 21.3095479910107 units
Strategy 1
Average (rms) distance between Controlpoints
after 4 iteration(s): 19.2419411315613 units
Strategy 1
Average (rms) distance between Controlpoints
after 5 iteration(s): 12.014503265537 units
Strategy 1
Average (rms) distance between Controlpoints
after 6 iteration(s): 11.4781410444244 units
Strategy 1
Average (rms) distance between Controlpoints
after 7 iteration(s): 6.13740834520267 units
Strategy 1
Average (rms) distance between Controlpoints
after 8 iteration(s): 4.69129004132988 units
Strategy 1
Average (rms) distance between Controlpoints
after 9 iteration(s): 4.53407231530812 units
Strategy 1
Average (rms) distance between Controlpoints
after 10 iteration(s): 4.53054983668731 units
Optimizing Variables
Strategy 2
Average (rms) distance between Controlpoints
after 0 iteration(s): 4.53055423265351 units
Strategy 2
Average (rms) distance between Controlpoints
after 1 iteration(s): 4.5233121510019 units
Strategy 2
Average (rms) distance between Controlpoints
after 2 iteration(s): 4.52330587534857 units
Strategy 2
Average (rms) distance between Controlpoints
after 3 iteration(s): 4.52330586987669 units
Optimizing Variables
Strategy 1
Average (rms) distance between Controlpoints
after 0 iteration(s): 1181.13077426794 units
Strategy 1
Average (rms) distance between Controlpoints
after 1 iteration(s): 91.9339923208928 units
Strategy 1
Average (rms) distance between Controlpoints
after 2 iteration(s): 32.7818563920828 units
Strategy 1
Average (rms) distance between Controlpoints
after 3 iteration(s): 6.69416206972883 units
Strategy 1
Average (rms) distance between Controlpoints
after 4 iteration(s): 6.59843887521794 units
Strategy 1
Average (rms) distance between Controlpoints
after 5 iteration(s): 6.51712746424085 units
Optimizing Variables
Strategy 2
Average (rms) distance between Controlpoints
after 0 iteration(s): 6.51714477249894 units
Strategy 2
Average (rms) distance between Controlpoints
after 1 iteration(s): 6.50644610117706 units
Strategy 2
Average (rms) distance between Controlpoints
after 2 iteration(s): 6.50644498466688 units
Optimizing Variables
Strategy 1
Average (rms) distance between Controlpoints
after 0 iteration(s): 1315.75209583191 units
Strategy 1
Average (rms) distance between Controlpoints
after 1 iteration(s): 579.420204915674 units
Strategy 1
Average (rms) distance between Controlpoints
after 2 iteration(s): 156.531547502369 units
Strategy 1
Average (rms) distance between Controlpoints
after 3 iteration(s): 84.5416336535399 units
Strategy 1
Average (rms) distance between Controlpoints
after 4 iteration(s): 58.4548024685542 units
Strategy 1
Average (rms) distance between Controlpoints
after 5 iteration(s): 25.595311327854 units
Strategy 1
Average (rms) distance between Controlpoints
after 6 iteration(s): 8.44586750942283 units
Strategy 1
Average (rms) distance between Controlpoints
after 7 iteration(s): 6.21325761405805 units
Strategy 1
Average (rms) distance between Controlpoints
after 8 iteration(s): 5.45483757041718 units
Strategy 1
Average (rms) distance between Controlpoints
after 9 iteration(s): 4.36029158097841 units
Strategy 1
Average (rms) distance between Controlpoints
after 10 iteration(s): 3.86299458928411 units
Strategy 1
Average (rms) distance between Controlpoints
after 11 iteration(s): 3.86299458928411 units
Optimizing Variables
Strategy 2
Average (rms) distance between Controlpoints
after 0 iteration(s): 3.86299651718787 units
Strategy 2
Average (rms) distance between Controlpoints
after 1 iteration(s): 3.85521710623802 units
Strategy 2
Average (rms) distance between Controlpoints
after 2 iteration(s): 3.85520369041837 units
Strategy 2
Average (rms) distance between Controlpoints
after 3 iteration(s): 3.8552036405997 units
Optimizing Variables
Strategy 1
Average (rms) distance between Controlpoints
after 0 iteration(s): 804.610878580804 units
Strategy 1
Average (rms) distance between Controlpoints
after 1 iteration(s): 405.407601892802 units
Strategy 1
Average (rms) distance between Controlpoints
after 2 iteration(s): 348.016937456304 units
Strategy 1
Average (rms) distance between Controlpoints
after 3 iteration(s): 301.17353633051 units
Strategy 1
Average (rms) distance between Controlpoints
after 4 iteration(s): 289.950557025166 units
Strategy 1
Average (rms) distance between Controlpoints
after 5 iteration(s): 279.41129181857 units
Strategy 1
Average (rms) distance between Controlpoints
after 6 iteration(s): 271.3311781295 units
Strategy 1
Average (rms) distance between Controlpoints
after 7 iteration(s): 243.809322183377 units
Strategy 1
Average (rms) distance between Controlpoints
after 8 iteration(s): 175.047591933761 units
Strategy 1
Average (rms) distance between Controlpoints
after 9 iteration(s): 110.28831762285 units
Strategy 1
Average (rms) distance between Controlpoints
after 10 iteration(s): 64.0888233001609 units
Strategy 1
Average (rms) distance between Controlpoints
after 11 iteration(s): 24.0611284002869 units
Strategy 1
Average (rms) distance between Controlpoints
after 12 iteration(s): 10.5564029104362 units
Strategy 1
Average (rms) distance between Controlpoints
after 13 iteration(s): 5.4254532412697 units
Strategy 1
Average (rms) distance between Controlpoints
after 14 iteration(s): 4.71050321632757 units
Strategy 1
Average (rms) distance between Controlpoints
after 15 iteration(s): 4.52670918227158 units
Strategy 1
Average (rms) distance between Controlpoints
after 16 iteration(s): 4.47535242060963 units
Optimizing Variables
Strategy 2
Average (rms) distance between Controlpoints
after 0 iteration(s): 4.47541069038615 units
Strategy 2
Average (rms) distance between Controlpoints
after 1 iteration(s): 4.46788262112503 units
Strategy 2
Average (rms) distance between Controlpoints
after 2 iteration(s): 4.46788105006841 units
Optimizing Variables
Strategy 1
Average (rms) distance between Controlpoints
after 0 iteration(s): 846.564749551665 units
Strategy 1
Average (rms) distance between Controlpoints
after 1 iteration(s): 286.48933802022 units
Strategy 1
Average (rms) distance between Controlpoints
after 2 iteration(s): 225.207482181276 units
Strategy 1
Average (rms) distance between Controlpoints
after 3 iteration(s): 219.040823842358 units
Strategy 1
Average (rms) distance between Controlpoints
after 4 iteration(s): 181.915385076296 units
Strategy 1
Average (rms) distance between Controlpoints
after 5 iteration(s): 164.253534956774 units
Strategy 1
Average (rms) distance between Controlpoints
after 6 iteration(s): 144.694092530782 units
Strategy 1
Average (rms) distance between Controlpoints
after 7 iteration(s): 127.561134920801 units
Strategy 1
Average (rms) distance between Controlpoints
after 8 iteration(s): 117.932028933636 units
Strategy 1
Average (rms) distance between Controlpoints
after 9 iteration(s): 115.450561670238 units
Strategy 1
Average (rms) distance between Controlpoints
after 10 iteration(s): 114.877582391637 units
Optimizing Variables
Strategy 2
Average (rms) distance between Controlpoints
after 0 iteration(s): 115.600549509034 units
Strategy 2
Average (rms) distance between Controlpoints
after 1 iteration(s): 115.525292838733 units
Strategy 2
Average (rms) distance between Controlpoints
after 2 iteration(s): 115.514439339128 units
Strategy 2
Average (rms) distance between Controlpoints
after 3 iteration(s): 115.50906179167 units
Strategy 2
Average (rms) distance between Controlpoints
after 4 iteration(s): 115.506326740245 units
Strategy 2
Average (rms) distance between Controlpoints
after 5 iteration(s): 115.504932491181 units
Strategy 2
Average (rms) distance between Controlpoints
after 6 iteration(s): 115.504220628421 units
Strategy 2
Average (rms) distance between Controlpoints
after 7 iteration(s): 115.503856767493 units
Strategy 2
Average (rms) distance between Controlpoints
after 8 iteration(s): 115.503670637634 units
Strategy 2
Average (rms) distance between Controlpoints
after 9 iteration(s): 115.503575370032 units
Strategy 2
Average (rms) distance between Controlpoints
after 10 iteration(s): 115.503526589721 units
Optimizing Variables
Strategy 1
Average (rms) distance between Controlpoints
after 0 iteration(s): 41.6729735658448 units
Strategy 1
Average (rms) distance between Controlpoints
after 1 iteration(s): 39.0737215287884 units
Strategy 1
Average (rms) distance between Controlpoints
after 2 iteration(s): 24.8810103610617 units
Strategy 1
Average (rms) distance between Controlpoints
after 3 iteration(s): 21.5587380306702 units
Strategy 1
Average (rms) distance between Controlpoints
after 4 iteration(s): 20.9727984489567 units
Strategy 1
Average (rms) distance between Controlpoints
after 5 iteration(s): 20.2159550834507 units
Strategy 1
Average (rms) distance between Controlpoints
after 6 iteration(s): 20.2159550834507 units
Optimizing Variables
Strategy 2
Average (rms) distance between Controlpoints
after 0 iteration(s): 20.2511517777318 units
Strategy 2
Average (rms) distance between Controlpoints
after 1 iteration(s): 19.5828809696517 units
Strategy 2
Average (rms) distance between Controlpoints
after 2 iteration(s): 19.5220969562332 units
Strategy 2
Average (rms) distance between Controlpoints
after 3 iteration(s): 19.5124925911918 units
Strategy 2
Average (rms) distance between Controlpoints
after 4 iteration(s): 19.5108436793826 units
Strategy 2
Average (rms) distance between Controlpoints
after 5 iteration(s): 19.51055067216 units
Strategy 2
Average (rms) distance between Controlpoints
after 6 iteration(s): 19.510497582519 units
Strategy 2
Average (rms) distance between Controlpoints
after 7 iteration(s): 19.5104878356888 units
Optimizing Variables
Strategy 1
Average (rms) distance between Controlpoints
after 0 iteration(s): 19.5021628391479 units
Strategy 1
Average (rms) distance between Controlpoints
after 1 iteration(s): 10.7705030199453 units
Strategy 1
Average (rms) distance between Controlpoints
after 2 iteration(s): 3.63205919392305 units
Strategy 1
Average (rms) distance between Controlpoints
after 3 iteration(s): 1.61458534803036 units
Strategy 1
Average (rms) distance between Controlpoints
after 4 iteration(s): 1.33750429886427 units
Strategy 1
Average (rms) distance between Controlpoints
after 5 iteration(s): 1.20597207267801 units
Strategy 1
Average (rms) distance between Controlpoints
after 6 iteration(s): 1.16318583330531 units
Strategy 1
Average (rms) distance between Controlpoints
after 7 iteration(s): 1.15511493737948 units
Strategy 1
Average (rms) distance between Controlpoints
after 8 iteration(s): 1.14286975633814 units
Optimizing Variables
Strategy 2
Average (rms) distance between Controlpoints
after 0 iteration(s): 1.14286981705038 units
Strategy 2
Average (rms) distance between Controlpoints
after 1 iteration(s): 1.12228772318994 units
Strategy 2
Average (rms) distance between Controlpoints
after 2 iteration(s): 1.12228625059904 units
Strategy 2
Average (rms) distance between Controlpoints
after 3 iteration(s): 1.12228625059904 units
Skipping automatic leveling because of existing vertical control points.
loading: ./8.jpg
downscaling: 2560x1440 1280x720 640x360
loading: ./2.jpg
downscaling: 2560x1440 1280x720 640x360
loading: ./3.jpg
downscaling: 2560x1440 1280x720 640x360
loading: ./4.jpg
downscaling: 2560x1440 1280x720 640x360
loading: ./1.jpg
downscaling: 2560x1440 1280x720 640x360
loading: ./7.jpg
downscaling: 2560x1440 1280x720 640x360
loading: ./5.jpg
downscaling: 2560x1440 1280x720 640x360
loading: ./6.jpg
downscaling: 2560x1440 1280x720 640x360
loading: ./9.jpg
downscaling: 2560x1440 1280x720 640x360
loading: ./10.jpg
downscaling: 2560x1440 1280x720 640x360
loading: ./12.jpg
downscaling: 2560x1440 1280x720 640x360
loading: ./11.jpg
downscaling: 2560x1440 1280x720 640x360
Sampling points
sampling points
extracting good points
Selected 2400 points
Photometric Optimization
Iteration: 0, error: 11.929990
Iteration: 1, error: 8.357341
Iteration: 2, error: 8.357341
Iteration: 3, error: 8.357341
Iteration: 4, error: 8.054073
Iteration: 5, error: 8.054073
Iteration: 6, error: 8.054073
Iteration: 7, error: 7.906340
Iteration: 8, error: 7.906340
Iteration: 9, error: 7.735570
Iteration: 10, error: 7.702098
Iteration: 11, error: 7.660811
Iteration: 12, error: 7.387559
Iteration: 13, error: 7.372245
Iteration: 14, error: 7.372245
Iteration: 15, error: 7.372245
Iteration: 16, error: 7.372245
Iteration: 17, error: 7.372110
Iteration: 18, error: 7.371576
Iteration: 19, error: 7.371171
Iteration: 20, error: 7.371171
Iteration: 21, error: 7.371171
Iteration: 22, error: 7.371171
Iteration: 23, error: 7.368819
Iteration: 24, error: 7.367812
Iteration: 25, error: 7.367240
Iteration: 26, error: 7.367077
Iteration: 27, error: 7.367047
Iteration: 28, error: 7.367043
Iteration: 29, error: 7.367042
Iteration: 30, error: 7.367042
Iteration: 31, error: 7.367042
Iteration: 32, error: 7.367042
Iteration: 33, error: 7.367042
Iteration: 34, error: 7.366924
Iteration: 35, error: 7.366907
Iteration: 36, error: 7.366900
Iteration: 37, error: 7.366897
Iteration: 38, error: 7.366896
Iteration: 39, error: 7.366896
Iteration: 40, error: 7.366896
Iteration: 41, error: 7.366896
Iteration: 42, error: 7.366896
Iteration: 43, error: 7.366896
Iteration: 44, error: 7.366896
Iteration: 45, error: 7.366896
Iteration: 46, error: 7.366896
Iteration: 47, error: 7.366896
Iteration: 48, error: 7.366896
Iteration: 49, error: 7.366896
Iteration: 50, error: 7.366896
Iteration: 51, error: 7.366883
Iteration: 52, error: 7.366883
Iteration: 53, error: 7.366883
Iteration: 54, error: 7.366883
Iteration: 55, error: 7.366882
Iteration: 56, error: 7.366882
Iteration: 57, error: 7.366881
Iteration: 58, error: 7.366881
Iteration: 59, error: 7.366880
Iteration: 60, error: 7.366880
Iteration: 61, error: 7.366880
Iteration: 62, error: 7.366880
Iteration: 63, error: 7.366880
Iteration: 64, error: 7.366880
Iteration: 65, error: 7.366880
Iteration: 66, error: 7.366879
Iteration: 67, error: 7.366879
Iteration: 68, error: 7.366879
Iteration: 69, error: 7.366879
Iteration: 70, error: 7.366879
Iteration: 71, error: 7.366879
Iteration: 72, error: 7.366878
Iteration: 73, error: 7.366877
Iteration: 74, error: 7.366876
Iteration: 75, error: 7.366876
Iteration: 76, error: 7.366876
Iteration: 77, error: 7.366876
Iteration: 78, error: 7.366876
Iteration: 79, error: 7.366876
Iteration: 80, error: 7.366876
Iteration: 81, error: 7.366876
Iteration: 82, error: 7.366876
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Iteration: 2, error: 7.220389
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Iteration: 4, error: 7.219363
Iteration: 5, error: 7.219221
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Iteration: 7, error: 7.217922
Iteration: 8, error: 7.216935
Iteration: 9, error: 7.216452
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Iteration: 15, error: 7.214825
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Iteration: 2, error: 6.979547
Iteration: 3, error: 6.969402
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Searching for best crop...
Calculate optimal size of panorama
Setting canvas size to 4476 x 1380
Searching for best crop rectangle
Run called
Inner 256 3885168: 0 4476 - 256 1124
Starting 256: 0 4476 - 256 1124
Starting 128: 0 4476 - 256 1124
Starting 64: 0 4476 - 256 1252
Starting 32: 0 4476 - 192 1316
Starting 16: 0 4476 - 160 1348
Starting 8: 0 4476 - 144 1348
Starting 4: 0 4476 - 144 1356
Starting 2: 0 4476 - 144 1356
Starting 1: 0 4476 - 142 1358
Set crop size to 0,141,4476,1359
Written output to ./output.pto
C:\Users\svrvs\Downloads\Feb24>
===========================================================
Step3
C:\Users\svrvs\Downloads\Feb24>hugin_executor --stitching --prefix=prefix
./output.pto
============================================
Stitching panorama...
============================================
Platform: Windows 10 (build 19045), 64-bit edition
Version: 2022.0.0.9bb147ae7161 built by Thomas
Working directory: C:\Users\svrvs\Downloads\Feb24
Output prefix: prefix
Blender: enblend 4.3-8243911d8684
ExifTool version: 12.50
Number of active images: 12
Output exposure value: 8.0
Canvas size: 4476x1380
ROI: (0, 141) - (4476, 1359)
FOV: 360x111
Projection: Equirectangular(2)
Using GPU for remapping: false
Panorama Outputs:
* Exposure corrected, low dynamic range
First input image
Number: 0
Filename: C:\Users\svrvs\Downloads\Feb24\1.jpg
Size: 2560x1440
Projection: Normal (rectilinear)
Response type: custom (EMoR)
HFOV: 103
Exposure value: 8.2
Remapping LDR images...
Multiple images output
loading 1.jpg
remapping 1.jpg
saving prefix0000.tif
loading 2.jpg
remapping 2.jpg
saving prefix0001.tif
loading 3.jpg
remapping 3.jpg
saving prefix0002.tif
loading 4.jpg
remapping 4.jpg
saving prefix0003.tif
loading 5.jpg
remapping 5.jpg
saving prefix0004.tif
loading 6.jpg
remapping 6.jpg
saving prefix0005.tif
loading 7.jpg
remapping 7.jpg
saving prefix0006.tif
loading 8.jpg
remapping 8.jpg
saving prefix0007.tif
loading 9.jpg
remapping 9.jpg
saving prefix0008.tif
loading 10.jpg
remapping 10.jpg
saving prefix0009.tif
loading 11.jpg
remapping 11.jpg
saving prefix0010.tif
loading 12.jpg
remapping 12.jpg
saving prefix0011.tif
Blending images...
enblend: warning: unable to run Dijkstra optimizer
enblend: note: seam-line end point outside of cost-image
enblend: note: contour #2 of 2, segment #1 of 1, vertex #131 of 131
enblend: warning: some images are redundant and will not be blended
enblend: note: usually this means that at least one of the images
enblend: note: does not belong to the set
Updating metadata...
1 image files updated
Removing temporary files
C:\Users\svrvs\Downloads\Feb24>
