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Visual model results

This directory contains real-model inference evidence for human review. Open the PNGs at full size to inspect boundaries, prompt placement, holes, and leakage. Blue is the selected mask for single-result families, green is a positive point/rectangle, and red is a negative point. SAM3 multi-instance results use distinct colors, contours, and numbers. Mock sessions are used only by isolated unit tests; no mocked image is presented here as quality evidence.

Open the cross-model contact sheet for a quick visual comparison, then inspect the linked full-resolution PNGs below.

Current verification status

Family Real artifacts produced in this change Validation
SAM ViT-B truck box, truck point, plants box, plants point, refined plant Official checkpoint, pinned source export, CPU ONNX
MobileSAM truck box, truck point, plants box, plants point, refined plant Official checkpoint, newly exported encoder and decoder, CPU ONNX
EfficientSAM-Ti truck box, truck point, plants box, plants point, refined plant Official Apache-2.0 split ONNX files, CPU ONNX
SAM 2.1 Tiny truck box, truck point, plants box, plants point, refined plant Official checkpoint, pinned source export, CPU ONNX
SAM 3 truck text, truck box selection, truck text + point, all 20 plants, top five plants, plants box selection, two-mark selection Latest official gated checkpoint, three newly exported ONNX graphs, official-style mask NMS, CPU ONNX

Older checked-in references remain under reference_sam/ and reference_sam2/. They are retained for comparison but are not counted as evidence that the current exporters ran successfully.

Numerical checks

  • SAM ViT-B PyTorch/ONNX mask IoU: truck box 0.9921, truck point 1.0000, plants box 0.9858, plants point 1.0000. Encoder embeddings had approximately 1e-7 mean absolute error and cosine similarity 1.0000.
  • MobileSAM PyTorch/ONNX mask IoU: truck box 0.9961, truck point 0.9188, plants box 0.9962, plants point 0.9945. The lower truck-point agreement is an ambiguous single-click/TinyViT case; both results visibly select the door.
  • SAM 2.1 Tiny PyTorch/ONNX mask IoU: truck box 0.99757, truck point 0.99576, plants box 0.99681, plants point 0.99761.
  • EfficientSAM-Ti mask area fractions: truck box 0.2921, truck point 0.0366, plants box 0.0324, plants point 0.0104. Both positive points are contained; box-mask pixels outside the prompt are 0.14% for truck and 0.02% for plants.
  • SAM 3 real CPU CLI runs retain one mask for truck text/box/text-plus-point, one mask for each plant geometry selection, 20 masks for text-only plant, and five when capped with --max_instances 5. Complete cold-process runs took 18.9–31.8 seconds and peaked at 8.2–8.5 GiB resident memory on this host.

The refined portrait prompt combines a tight rectangle with a positive point on the pot. Every tested family selects the intended whole plant/pot. SAM3 geometry still acts as a visual concept exemplar internally; the CLI's default auto mode now ranks prompt overlap and returns the best local match, while --sam3_output_mode all retains the broader concept-discovery behavior.

Run logs

Reproduce

bash download_all_models.sh
bash test_comprehensive.sh

Every future test writes both a PNG and sibling .log under visual_results/runs/ by default. Set SAMEXPORTER_RESULTS_DIR to another persistent path when comparing runs. Promote only reviewed representative outputs into a named family directory.