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Getting the edges right

Every room has details worth keeping. Explore three Rendero interiors at full size, then take a closer look at what our selection tests measured.

Three separate showcase images. The measured benchmark below uses a different set of photos.

About these images

These are three separate AI-generated interior images supplied by Rendero. They show different room layouts, not an original and two outputs from the same scene. No segmentation masks, test scores or rendering settings were supplied for them. The original files credit “Made with Google AI”. Lossless web copies preserve their original pixels. Image source record.

The measured selection test

The interiors above are showcase images. These results come from a separate set of 50 public photos used during development on 3 September 2026: 30 objects and 20 wall areas. The test measures selection cleanup, not finished renders or today’s product.

The September test version followed the labelled edges a little more closely on average. It also selected slightly more unwanted area. These two measurements need to be read together.

Edge match

How closely the selection follows the labelled outline. A score out of 100.

Higher is better · all 50 photos
Original selection49.13 /100
September test version51.47 /100

Original → September test: +2.34 points (better). 37 improved · 13 declined · 0 tied.

Extra area selected

The share of the selection that falls outside the labelled target.

Lower is better · all 50 photos
Original selection10.83%
September test version11.03%

Original → September test: +0.20 percentage points (worse). 20 improved · 30 declined · 0 tied.

Edge scores improved on 37 photos and fell on 13. Extra-area errors increased on 30 photos. An earlier cleanup version scored slightly better on all four averages than the September test version.

We did not adopt the proposed update. It changed none of the 50 selections, and the test still fell short of our recorded edge-match and missed-area requirements. The full results and thresholds are below.

Inspect three test photos and their selections

A small change, a larger improvement and a setback

These are examples from the measured set, chosen to show different outcomes. They are not a representative sample of all 50 photos.

Purple shows each saved selection; the purple-and-white line follows its boundary. Reference outline and Changed pixels are optional inspection views. The photos and mask geometry are unchanged. Each pair shows the full image at the same scale. Reconstructed after-selections match all four recorded scores exactly.

Example 1 of 3

A small change around the oven

Original selection
Two ovens and stainless-steel worktops in a kitchen; the left-hand oven is the test target.

Edge match 82.37 /100Extra area selected 4.34%

September test version
Two ovens and stainless-steel worktops in a kitchen; the left-hand oven is the test target.

Edge match 83.96 /100Extra area selected 4.21%

Changed pixels: 169. Pink marks pixels added to or removed from the selection, at their exact size. Both photos show the same diagnostic. Other overlays are hidden until this view is switched off.

The target is the oven on the left. Cleanup changes which 169 pixels are selected, with a modest increase in the edge score. Most of the selection stays the same.

Why this example: A change close to the middle of the 50 recorded edge-score changes.

Photo: Kitchen YHA Rowen by Eric Audige-Soutter, CC BY 2.0. Unmodified COCO source photo; selection overlays added by Rendero. Reference outline rendered as SVG from COCO Consortium labels, CC BY 4.0.

Photo and selection record

COCO image 175364 · 614 × 461 pixels · 169 selection pixels changed. The after-selection is a deterministic reconstruction from the saved inputs and historical cleanup code; every remeasured score matches the original record exactly.

Open the original photo · Original selection · Tested selection · Dataset reference · Full photo evidence record

Example 2 of 3

Fewer gaps in the wall selection

Original selection
A boat under a masonry arch, with the wall behind it used as the test target.

Edge match 26.21 /100Extra area selected 2.74%

September test version
A boat under a masonry arch, with the wall behind it used as the test target.

Edge match 55.23 /100Extra area selected 2.35%

Changed pixels: 9,492. Pink marks pixels added to or removed from the selection, at their exact size. Both photos show the same diagnostic. Other overlays are hidden until this view is switched off.

Look at the wall behind the boat. Cleanup fills many small gaps in the selected area. Its edge score improves, although part of the reference area is still missed.

Why this example: The largest edge-score improvement in this test; it is an example of a strong result.

Photo: Parked Boat by Charles Hutchins, CC BY 2.0. Unmodified COCO source photo; selection overlays added by Rendero. Reference outline rendered as SVG from Holger Caesar, Jasper Uijlings and Vittorio Ferrari / COCO-Stuff labels, CC BY 4.0.

Photo and selection record

COCO image 113051 · 640 × 480 pixels · 9,492 selection pixels changed. The after-selection is a deterministic reconstruction from the saved inputs and historical cleanup code; every remeasured score matches the original record exactly.

Open the original photo · Original selection · Tested selection · Dataset reference · Full photo evidence record

Example 3 of 3

An edge score that went backwards

Original selection
A refrigerator on the left of a kitchen with timber cabinets and a cooker.

Edge match 69.10 /100Extra area selected 3.30%

September test version
A refrigerator on the left of a kitchen with timber cabinets and a cooker.

Edge match 64.26 /100Extra area selected 3.44%

Changed pixels: 221. Pink marks pixels added to or removed from the selection, at their exact size. Both photos show the same diagnostic. Other overlays are hidden until this view is switched off.

The refrigerator is on the far left. Both selections look similar at this scale, but 221 pixels change selection status and the edge score falls. The numbers catch a setback that is easy to miss at a glance.

Why this example: A case with a lower edge score after cleanup, included to show a setback.

Photo: Kitchen by marysalome, CC BY 2.0. Unmodified COCO source photo; selection overlays added by Rendero. Reference outline rendered as SVG from COCO Consortium labels, CC BY 4.0.

Photo and selection record

COCO image 429598 · 640 × 480 pixels · 221 selection pixels changed. The after-selection is a deterministic reconstruction from the saved inputs and historical cleanup code; every remeasured score matches the original record exactly.

Open the original photo · Original selection · Tested selection · Dataset reference · Full photo evidence record

Compare all five versions and four measurements

All charts use a fixed zero-to-100 scale. Scores are averages with equal weight for each photo. Filter objects and walls to inspect a subset.

Showing all 50 cases. Charts and per-case rows use the same selection.

Area match

How closely the selection overlaps the labelled target.

Higher is better · mean of selected cases
Original selection75.42%
Earlier cleanup75.96%
Cleanup with shape checks75.80%
September test version75.80%
Proposed update · not adopted75.80%

Original → September test: +0.39 percentage points (better). 35 improved · 15 declined · 0 tied.

Edge match

How closely the selection follows the labelled outline. A score out of 100.

Higher is better · mean of selected cases
Original selection49.13 /100
Earlier cleanup51.83 /100
Cleanup with shape checks51.47 /100
September test version51.47 /100
Proposed update · not adopted51.47 /100

Original → September test: +2.34 points (better). 37 improved · 13 declined · 0 tied.

Extra area selected

The share of the selection that falls outside the labelled target.

Lower is better · mean of selected cases
Original selection10.83%
Earlier cleanup11.02%
Cleanup with shape checks11.03%
September test version11.03%
Proposed update · not adopted11.03%

Original → September test: +0.20 percentage points (worse). 20 improved · 30 declined · 0 tied.

Target area missed

The share of the labelled target left out of the selection.

Lower is better · mean of selected cases
Original selection20.89%
Earlier cleanup20.30%
Cleanup with shape checks20.47%
September test version20.47%
Proposed update · not adopted20.47%

Original → September test: −0.42 percentage points (better). 42 improved · 8 declined · 0 tied.

The shape-check version, September test version and proposed update have identical scores on this set. Version identifiers are recorded in the technical details below.

How we tested

Test date
3 September 2026. We replayed cleanup on saved selections; the image model was not run again.
Sample
50 distinct COCO validation images: 30 object instances and 20 COCO-Stuff wall surfaces. All reused in development.
Same starting point
Every cleanup version received the same original photo, saved selection and model confidence value.
Image resolution
Native widths 320–640 px and heights 240–640 px. No resizing during replay.
What counts as correct
The labelled target in COCO or COCO-Stuff. Its location was supplied in advance, with 5% padding around its box. This tests cleanup after an object has been located.
Limits
These photos had already informed development. They do not establish performance on new projects. We did not measure finished renders, automatic object finding, speed, cost or other products.
Technical details: scores, versions and test requirements

The saved image model was SAM 2 Hiera Large via RSAM, with mode sam2_compat and operation parent_masks_v1. These identifiers describe the historical test configuration.

Chart names and source versions: Original selection = saved raw parent mask; Earlier cleanup = 9317364; Cleanup with shape checks = 91b8f00; September test version = 5ceddcf; Proposed update = the unpromoted line-recovery candidate. Exact source hashes and encoder/decoder revisions are in the full specification.

Test requirements: the proposed update’s mean edge score was 51.47 /100, below the required 68.00 /100. Its missed-area rate was 20.47%, above the 18.00% limit. These are full-set values; the complete registered requirements are in the specification.

Reader-facing names map to the recorded metrics as follows: area match = intersection over union (IoU); edge match = boundary F1; extra area selected = leakage; target area missed = missed rate.

Prediction masks are binarized above 127. Reference masks have the same native dimensions. Source scores range from 0 to 1. Edge match is shown out of 100; other ratios are shown as percentages.

IoU = intersection pixels / union pixels Leakage = false-positive pixels / predicted foreground pixels Missed area = false-negative pixels / reference foreground pixels

Each denominator is clamped to at least 1. Boundary F1 is the harmonic mean of boundary precision and recall. Boundaries use four-connected erosion; the outer image border counts as boundary. Matches use a 5 × 5 square max filter: Chebyshev distance ≤ 2 native pixels. Two empty boundaries score 1; otherwise an absent boundary receives zero match credit.

Reported mean F1 is the average of the 50 individual F1 scores. It is not F1 calculated from pooled or averaged precision and recall. Paired changes within 10−12 count as ties. Changes on the out-of-100 edge scale are points; changes in percentage ratios are percentage points. Both equal the difference in the original scores multiplied by 100.

Versions, input provenance and reproducibility limits

The historical refiners are identified by revisions 9317364, 91b8f00 and 5ceddcf. The opt-in recovery candidate was not deployed. Exact refiner-source hashes and the saved upstream encoder and decoder revisions are recorded in the full specification.

Reference pixel masks were not passed to inference, but their bounds supplied the localization boxes. This controls localization out of the comparison. COCO labels are independent of the predictions, but they do not provide detailed CAD geometry or fine alpha-matte truth.

The fixture originally assigned 30 diagnosis cases and 20 holdouts. All 50 were later reused; those labels now describe provenance only. Results are descriptive, with no untouched confirmation set, confidence interval or statistical-significance claim.

All 50 saved-response hashes were checked. The exported per-case records independently reproduce all 20 recorded mean scores and 12 paired comparisons. For the three photo examples only, we also reconstructed the September cleanup from the saved inputs and original source code, then remeasured all four scores: each matches the saved record exactly. This did not rerun image-model inference or independently confirm the remaining 47 cases from pixels.

Hardware, the complete model-weight digest and full upstream inference settings were not recorded. The score downloads contain derived results and metadata; the three licensed photo examples and separate SVG overlays are additional evidence on this page.

Every case, including the regressions

The table includes all five stages for every image. Filters above apply to these rows too. Full-precision values and reference identifiers are available in the downloads.

Open the per-case score table · 250 rows for 50 images
Historical selection scores for all five versions of each photo. Edge match is out of 100; other ratios are percentages. Area and edge match: higher is better. Extra and missed area: lower is better.
COCO imageCategoryTrackVersionArea match ↑Edge match /100 ↑Extra area ↓Missed area ↓
1993bedobjectOriginal selection86.66%51.36 /1000.46%12.99%
1993bedobjectEarlier cleanup86.54%52.39 /1000.48%13.10%
1993bedobjectCleanup with shape checks86.54%52.39 /1000.48%13.10%
1993bedobjectSeptember test version86.54%52.39 /1000.48%13.10%
1993bedobjectProposed update · not adopted86.54%52.39 /1000.48%13.10%
10092bedobjectOriginal selection5.59%21.30 /1007.95%94.39%
10092bedobjectEarlier cleanup5.64%22.10 /1007.72%94.33%
10092bedobjectCleanup with shape checks5.64%22.10 /1007.72%94.33%
10092bedobjectSeptember test version5.64%22.10 /1007.72%94.33%
10092bedobjectProposed update · not adopted5.64%22.10 /1007.72%94.33%
464358bedobjectOriginal selection63.85%9.04 /10011.43%30.41%
464358bedobjectEarlier cleanup64.02%8.62 /10011.40%30.24%
464358bedobjectCleanup with shape checks64.02%8.62 /10011.40%30.24%
464358bedobjectSeptember test version64.02%8.62 /10011.40%30.24%
464358bedobjectProposed update · not adopted64.02%8.62 /10011.40%30.24%
340451benchobjectOriginal selection60.06%55.90 /1001.52%39.38%
340451benchobjectEarlier cleanup60.48%57.96 /1001.48%38.97%
340451benchobjectCleanup with shape checks60.20%57.28 /1001.49%39.25%
340451benchobjectSeptember test version60.20%57.28 /1001.49%39.25%
340451benchobjectProposed update · not adopted60.20%57.28 /1001.49%39.25%
221502benchobjectOriginal selection82.86%63.20 /1000.18%17.02%
221502benchobjectEarlier cleanup83.32%64.43 /1000.22%16.53%
221502benchobjectCleanup with shape checks83.32%64.43 /1000.22%16.53%
221502benchobjectSeptember test version83.32%64.43 /1000.22%16.53%
221502benchobjectProposed update · not adopted83.32%64.43 /1000.22%16.53%
420916benchobjectOriginal selection48.86%46.51 /1004.57%49.97%
420916benchobjectEarlier cleanup50.14%49.71 /1004.10%48.76%
420916benchobjectCleanup with shape checks49.26%48.37 /1004.17%49.66%
420916benchobjectSeptember test version49.26%48.37 /1004.17%49.66%
420916benchobjectProposed update · not adopted49.26%48.37 /1004.17%49.66%
27620chairobjectOriginal selection90.41%62.55 /1005.80%4.27%
27620chairobjectEarlier cleanup90.06%60.48 /1006.21%4.23%
27620chairobjectCleanup with shape checks90.06%60.48 /1006.21%4.23%
27620chairobjectSeptember test version90.06%60.48 /1006.21%4.23%
27620chairobjectProposed update · not adopted90.06%60.48 /1006.21%4.23%
546964chairobjectOriginal selection92.15%51.36 /1003.32%4.84%
546964chairobjectEarlier cleanup92.71%52.96 /1003.37%4.19%
546964chairobjectCleanup with shape checks92.08%51.20 /1003.39%4.85%
546964chairobjectSeptember test version92.08%51.20 /1003.39%4.85%
546964chairobjectProposed update · not adopted92.08%51.20 /1003.39%4.85%
189820chairobjectOriginal selection73.59%36.61 /1003.53%24.38%
189820chairobjectEarlier cleanup73.43%37.10 /1003.33%24.67%
189820chairobjectCleanup with shape checks73.43%37.10 /1003.33%24.67%
189820chairobjectSeptember test version73.43%37.10 /1003.33%24.67%
189820chairobjectProposed update · not adopted73.43%37.10 /1003.33%24.67%
356432couchobjectOriginal selection79.73%56.45 /1000.89%19.69%
356432couchobjectEarlier cleanup80.01%58.38 /1000.94%19.38%
356432couchobjectCleanup with shape checks80.01%58.38 /1000.94%19.38%
356432couchobjectSeptember test version80.01%58.38 /1000.94%19.38%
356432couchobjectProposed update · not adopted80.01%58.38 /1000.94%19.38%
31735couchobjectOriginal selection89.80%61.10 /1000.97%9.40%
31735couchobjectEarlier cleanup90.25%63.52 /1001.10%8.84%
31735couchobjectCleanup with shape checks90.25%63.52 /1001.10%8.84%
31735couchobjectSeptember test version90.25%63.52 /1001.10%8.84%
31735couchobjectProposed update · not adopted90.25%63.52 /1001.10%8.84%
232088couchobjectOriginal selection84.18%17.44 /1004.71%12.17%
232088couchobjectEarlier cleanup86.16%19.02 /1004.75%9.97%
232088couchobjectCleanup with shape checks84.06%17.14 /1004.87%12.16%
232088couchobjectSeptember test version84.06%17.14 /1004.87%12.16%
232088couchobjectProposed update · not adopted84.06%17.14 /1004.87%12.16%
398652dining tableobjectOriginal selection72.26%35.29 /10012.05%19.80%
398652dining tableobjectEarlier cleanup73.17%43.26 /10010.83%19.69%
398652dining tableobjectCleanup with shape checks73.17%43.26 /10010.83%19.69%
398652dining tableobjectSeptember test version73.17%43.26 /10010.83%19.69%
398652dining tableobjectProposed update · not adopted73.17%43.26 /10010.83%19.69%
397133dining tableobjectOriginal selection50.72%30.51 /1002.69%48.56%
397133dining tableobjectEarlier cleanup50.84%31.32 /1002.63%48.45%
397133dining tableobjectCleanup with shape checks50.84%31.32 /1002.63%48.45%
397133dining tableobjectSeptember test version50.84%31.32 /1002.63%48.45%
397133dining tableobjectProposed update · not adopted50.84%31.32 /1002.63%48.45%
256916dining tableobjectOriginal selection87.71%70.35 /1007.45%5.62%
256916dining tableobjectEarlier cleanup87.86%71.92 /1008.04%4.83%
256916dining tableobjectCleanup with shape checks87.86%71.92 /1008.04%4.83%
256916dining tableobjectSeptember test version87.86%71.92 /1008.04%4.83%
256916dining tableobjectProposed update · not adopted87.86%71.92 /1008.04%4.83%
365766ovenobjectOriginal selection85.43%63.71 /10010.50%5.06%
365766ovenobjectEarlier cleanup85.37%63.63 /10010.58%5.03%
365766ovenobjectCleanup with shape checks85.37%63.63 /10010.58%5.03%
365766ovenobjectSeptember test version85.37%63.63 /10010.58%5.03%
365766ovenobjectProposed update · not adopted85.37%63.63 /10010.58%5.03%
175364ovenobjectOriginal selection94.09%82.37 /1004.34%1.72%
175364ovenobjectEarlier cleanup94.37%83.96 /1004.21%1.55%
175364ovenobjectCleanup with shape checks94.37%83.96 /1004.21%1.55%
175364ovenobjectSeptember test version94.37%83.96 /1004.21%1.55%
175364ovenobjectProposed update · not adopted94.37%83.96 /1004.21%1.55%
424349ovenobjectOriginal selection82.05%49.77 /1003.39%15.51%
424349ovenobjectEarlier cleanup82.54%58.69 /1003.35%15.03%
424349ovenobjectCleanup with shape checks82.54%58.69 /1003.35%15.03%
424349ovenobjectSeptember test version82.54%58.69 /1003.35%15.03%
424349ovenobjectProposed update · not adopted82.54%58.69 /1003.35%15.03%
437514potted plantobjectOriginal selection76.02%12.63 /1003.24%22.00%
437514potted plantobjectEarlier cleanup76.74%14.28 /1003.08%21.35%
437514potted plantobjectCleanup with shape checks76.52%14.00 /1003.08%21.57%
437514potted plantobjectSeptember test version76.52%14.00 /1003.08%21.57%
437514potted plantobjectProposed update · not adopted76.52%14.00 /1003.08%21.57%
569700potted plantobjectOriginal selection80.15%31.55 /1008.75%13.19%
569700potted plantobjectEarlier cleanup80.77%36.65 /1008.65%12.54%
569700potted plantobjectCleanup with shape checks80.10%35.40 /1008.71%13.27%
569700potted plantobjectSeptember test version80.10%35.40 /1008.71%13.27%
569700potted plantobjectProposed update · not adopted80.10%35.40 /1008.71%13.27%
404484potted plantobjectOriginal selection0.27%13.10 /10095.89%99.71%
404484potted plantobjectEarlier cleanup0.17%5.42 /10097.21%99.82%
404484potted plantobjectCleanup with shape checks0.17%5.42 /10097.21%99.82%
404484potted plantobjectSeptember test version0.17%5.42 /10097.21%99.82%
404484potted plantobjectProposed update · not adopted0.17%5.42 /10097.21%99.82%
429598refrigeratorobjectOriginal selection96.11%69.10 /1003.30%0.63%
429598refrigeratorobjectEarlier cleanup96.07%64.26 /1003.44%0.53%
429598refrigeratorobjectCleanup with shape checks96.07%64.26 /1003.44%0.53%
429598refrigeratorobjectSeptember test version96.07%64.26 /1003.44%0.53%
429598refrigeratorobjectProposed update · not adopted96.07%64.26 /1003.44%0.53%
313130refrigeratorobjectOriginal selection96.00%65.78 /1003.10%0.95%
313130refrigeratorobjectEarlier cleanup96.18%68.06 /1003.10%0.77%
313130refrigeratorobjectCleanup with shape checks96.18%68.06 /1003.10%0.77%
313130refrigeratorobjectSeptember test version96.18%68.06 /1003.10%0.77%
313130refrigeratorobjectProposed update · not adopted96.18%68.06 /1003.10%0.77%
52996refrigeratorobjectOriginal selection95.30%76.47 /1001.32%3.47%
52996refrigeratorobjectEarlier cleanup95.20%72.96 /1001.52%3.38%
52996refrigeratorobjectCleanup with shape checks95.20%72.96 /1001.52%3.38%
52996refrigeratorobjectSeptember test version95.20%72.96 /1001.52%3.38%
52996refrigeratorobjectProposed update · not adopted95.20%72.96 /1001.52%3.38%
241319sinkobjectOriginal selection92.10%68.99 /1005.76%2.41%
241319sinkobjectEarlier cleanup91.90%71.08 /1006.13%2.23%
241319sinkobjectCleanup with shape checks91.90%71.08 /1006.13%2.23%
241319sinkobjectSeptember test version91.90%71.08 /1006.13%2.23%
241319sinkobjectProposed update · not adopted91.90%71.08 /1006.13%2.23%
569917sinkobjectOriginal selection66.08%13.55 /10019.58%21.24%
569917sinkobjectEarlier cleanup67.25%12.74 /10019.48%19.68%
569917sinkobjectCleanup with shape checks66.64%12.35 /10019.62%20.40%
569917sinkobjectSeptember test version66.64%12.35 /10019.62%20.40%
569917sinkobjectProposed update · not adopted66.64%12.35 /10019.62%20.40%
223789sinkobjectOriginal selection90.09%39.18 /1007.85%2.42%
223789sinkobjectEarlier cleanup90.03%43.45 /1007.93%2.41%
223789sinkobjectCleanup with shape checks90.03%43.45 /1007.93%2.41%
223789sinkobjectSeptember test version90.03%43.45 /1007.93%2.41%
223789sinkobjectProposed update · not adopted90.03%43.45 /1007.93%2.41%
371529toiletobjectOriginal selection88.62%51.97 /1003.05%8.84%
371529toiletobjectEarlier cleanup88.93%56.07 /1002.86%8.68%
371529toiletobjectCleanup with shape checks88.93%56.07 /1002.86%8.68%
371529toiletobjectSeptember test version88.93%56.07 /1002.86%8.68%
371529toiletobjectProposed update · not adopted88.93%56.07 /1002.86%8.68%
234413toiletobjectOriginal selection93.91%59.82 /1001.78%4.46%
234413toiletobjectEarlier cleanup94.04%57.16 /1001.85%4.27%
234413toiletobjectCleanup with shape checks94.04%57.16 /1001.85%4.27%
234413toiletobjectSeptember test version94.04%57.16 /1001.85%4.27%
234413toiletobjectProposed update · not adopted94.04%57.16 /1001.85%4.27%
537812toiletobjectOriginal selection95.21%87.91 /1003.14%1.76%
537812toiletobjectEarlier cleanup95.07%87.65 /1002.94%2.11%
537812toiletobjectCleanup with shape checks95.07%87.65 /1002.94%2.11%
537812toiletobjectSeptember test version95.07%87.65 /1002.94%2.11%
537812toiletobjectProposed update · not adopted95.07%87.65 /1002.94%2.11%
39956wall-bricksurfaceOriginal selection95.48%66.39 /1001.05%3.54%
39956wall-bricksurfaceEarlier cleanup95.72%66.98 /1001.09%3.26%
39956wall-bricksurfaceCleanup with shape checks95.72%66.98 /1001.09%3.26%
39956wall-bricksurfaceSeptember test version95.72%66.98 /1001.09%3.26%
39956wall-bricksurfaceProposed update · not adopted95.72%66.98 /1001.09%3.26%
124659wall-bricksurfaceOriginal selection66.10%45.41 /10021.22%19.58%
124659wall-bricksurfaceEarlier cleanup66.96%51.57 /10021.62%17.87%
124659wall-bricksurfaceCleanup with shape checks66.96%51.57 /10021.62%17.87%
124659wall-bricksurfaceSeptember test version66.96%51.57 /10021.62%17.87%
124659wall-bricksurfaceProposed update · not adopted66.96%51.57 /10021.62%17.87%
281032wall-bricksurfaceOriginal selection93.10%65.83 /1000.46%6.49%
281032wall-bricksurfaceEarlier cleanup93.27%65.93 /1000.54%6.25%
281032wall-bricksurfaceCleanup with shape checks93.27%65.93 /1000.54%6.25%
281032wall-bricksurfaceSeptember test version93.27%65.93 /1000.54%6.25%
281032wall-bricksurfaceProposed update · not adopted93.27%65.93 /1000.54%6.25%
415194wall-concretesurfaceOriginal selection88.04%58.20 /1003.81%8.78%
415194wall-concretesurfaceEarlier cleanup89.07%60.34 /1003.91%7.58%
415194wall-concretesurfaceCleanup with shape checks89.07%60.34 /1003.91%7.58%
415194wall-concretesurfaceSeptember test version89.07%60.34 /1003.91%7.58%
415194wall-concretesurfaceProposed update · not adopted89.07%60.34 /1003.91%7.58%
148620wall-concretesurfaceOriginal selection96.67%87.51 /1000.52%2.84%
148620wall-concretesurfaceEarlier cleanup97.04%89.24 /1000.59%2.40%
148620wall-concretesurfaceCleanup with shape checks97.04%89.24 /1000.59%2.40%
148620wall-concretesurfaceSeptember test version97.04%89.24 /1000.59%2.40%
148620wall-concretesurfaceProposed update · not adopted97.04%89.24 /1000.59%2.40%
367569wall-concretesurfaceOriginal selection78.68%46.81 /1000.93%20.74%
367569wall-concretesurfaceEarlier cleanup79.27%48.24 /1001.03%20.06%
367569wall-concretesurfaceCleanup with shape checks79.27%48.24 /1001.03%20.06%
367569wall-concretesurfaceSeptember test version79.27%48.24 /1001.03%20.06%
367569wall-concretesurfaceProposed update · not adopted79.27%48.24 /1001.03%20.06%
292005wall-othersurfaceOriginal selection90.39%58.40 /1007.71%2.23%
292005wall-othersurfaceEarlier cleanup90.58%64.51 /1007.89%1.80%
292005wall-othersurfaceCleanup with shape checks90.58%64.51 /1007.89%1.80%
292005wall-othersurfaceSeptember test version90.58%64.51 /1007.89%1.80%
292005wall-othersurfaceProposed update · not adopted90.58%64.51 /1007.89%1.80%
329080wall-othersurfaceOriginal selection94.85%81.04 /1000.85%4.37%
329080wall-othersurfaceEarlier cleanup95.00%80.92 /1001.02%4.06%
329080wall-othersurfaceCleanup with shape checks95.00%80.92 /1001.02%4.06%
329080wall-othersurfaceSeptember test version95.00%80.92 /1001.02%4.06%
329080wall-othersurfaceProposed update · not adopted95.00%80.92 /1001.02%4.06%
577584wall-othersurfaceOriginal selection94.18%80.79 /1001.96%4.02%
577584wall-othersurfaceEarlier cleanup94.46%82.38 /1002.09%3.60%
577584wall-othersurfaceCleanup with shape checks94.46%82.38 /1002.09%3.60%
577584wall-othersurfaceSeptember test version94.46%82.38 /1002.09%3.60%
577584wall-othersurfaceProposed update · not adopted94.46%82.38 /1002.09%3.60%
529762wall-panelsurfaceOriginal selection45.74%37.38 /1000.49%54.16%
529762wall-panelsurfaceEarlier cleanup46.21%44.31 /1000.25%53.74%
529762wall-panelsurfaceCleanup with shape checks46.21%44.31 /1000.25%53.74%
529762wall-panelsurfaceSeptember test version46.21%44.31 /1000.25%53.74%
529762wall-panelsurfaceProposed update · not adopted46.21%44.31 /1000.25%53.74%
13659wall-panelsurfaceOriginal selection48.62%29.30 /10015.16%46.76%
13659wall-panelsurfaceEarlier cleanup50.48%32.52 /10011.96%45.80%
13659wall-panelsurfaceCleanup with shape checks50.48%32.52 /10011.96%45.80%
13659wall-panelsurfaceSeptember test version50.48%32.52 /10011.96%45.80%
13659wall-panelsurfaceProposed update · not adopted50.48%32.52 /10011.96%45.80%
75612wall-panelsurfaceOriginal selection94.82%70.32 /1003.81%1.47%
75612wall-panelsurfaceEarlier cleanup95.07%71.92 /1003.75%1.27%
75612wall-panelsurfaceCleanup with shape checks95.07%71.92 /1003.75%1.27%
75612wall-panelsurfaceSeptember test version95.07%71.92 /1003.75%1.27%
75612wall-panelsurfaceProposed update · not adopted95.07%71.92 /1003.75%1.27%
65350wall-stonesurfaceOriginal selection80.43%37.13 /10011.83%9.83%
65350wall-stonesurfaceEarlier cleanup81.16%45.37 /10011.84%8.91%
65350wall-stonesurfaceCleanup with shape checks81.16%45.37 /10011.84%8.91%
65350wall-stonesurfaceSeptember test version81.16%45.37 /10011.84%8.91%
65350wall-stonesurfaceProposed update · not adopted81.16%45.37 /10011.84%8.91%
113051wall-stonesurfaceOriginal selection78.91%26.21 /1002.74%19.29%
113051wall-stonesurfaceEarlier cleanup84.69%63.63 /1002.31%13.58%
113051wall-stonesurfaceCleanup with shape checks83.27%55.23 /1002.35%15.03%
113051wall-stonesurfaceSeptember test version83.27%55.23 /1002.35%15.03%
113051wall-stonesurfaceProposed update · not adopted83.27%55.23 /1002.35%15.03%
526103wall-stonesurfaceOriginal selection85.79%52.67 /1001.54%13.04%
526103wall-stonesurfaceEarlier cleanup86.68%59.60 /1002.02%11.74%
526103wall-stonesurfaceCleanup with shape checks86.40%58.58 /1002.02%12.03%
526103wall-stonesurfaceSeptember test version86.40%58.58 /1002.02%12.03%
526103wall-stonesurfaceProposed update · not adopted86.40%58.58 /1002.02%12.03%
393569wall-tilesurfaceOriginal selection74.74%42.55 /10019.48%8.75%
393569wall-tilesurfaceEarlier cleanup76.53%46.55 /10018.51%7.37%
393569wall-tilesurfaceCleanup with shape checks76.53%46.55 /10018.51%7.37%
393569wall-tilesurfaceSeptember test version76.53%46.55 /10018.51%7.37%
393569wall-tilesurfaceProposed update · not adopted76.53%46.55 /10018.51%7.37%
570736wall-tilesurfaceOriginal selection68.62%35.11 /10018.30%18.92%
570736wall-tilesurfaceEarlier cleanup71.09%42.60 /10017.32%16.47%
570736wall-tilesurfaceCleanup with shape checks70.16%41.70 /10017.51%17.56%
570736wall-tilesurfaceSeptember test version70.16%41.70 /10017.51%17.56%
570736wall-tilesurfaceProposed update · not adopted70.16%41.70 /10017.51%17.56%
90108wall-tilesurfaceOriginal selection0.07%9.10 /10099.79%99.90%
90108wall-tilesurfaceEarlier cleanup0.02%11.20 /10099.94%99.97%
90108wall-tilesurfaceCleanup with shape checks0.02%11.20 /10099.94%99.97%
90108wall-tilesurfaceSeptember test version0.02%11.20 /10099.94%99.97%
90108wall-tilesurfaceProposed update · not adopted0.02%11.20 /10099.94%99.97%
458410wall-woodsurfaceOriginal selection0.36%2.42 /10086.42%99.64%
458410wall-woodsurfaceEarlier cleanup0.01%1.26 /10099.42%99.99%
458410wall-woodsurfaceCleanup with shape checks0.01%1.26 /10099.42%99.99%
458410wall-woodsurfaceSeptember test version0.01%1.26 /10099.42%99.99%
458410wall-woodsurfaceProposed update · not adopted0.01%1.26 /10099.42%99.99%
402720wall-woodsurfaceOriginal selection95.32%69.00 /1000.82%3.92%
402720wall-woodsurfaceEarlier cleanup95.58%72.96 /1000.84%3.64%
402720wall-woodsurfaceCleanup with shape checks95.58%72.96 /1000.84%3.64%
402720wall-woodsurfaceSeptember test version95.58%72.96 /1000.84%3.64%
402720wall-woodsurfaceProposed update · not adopted95.58%72.96 /1000.84%3.64%

Download the evidence

Original datasets: COCO and COCO-Stuff · COCO-Stuff label definitions · SAM 2 upstream project.

The original eight-file download contains scores, public image identifiers and source hashes. Three separately credited test photos and selection overlays can be inspected above. The Rendero showcase images are separate and have no benchmark scores. No private account data are included.

Explore AI rendering workflows · About Rendero · More research and guides

Interior detail

Separate showcase image. The original pixels are preserved.