Implements and validates video quality metrics (FID, CLIPSIM, temporal consistency) for VideoQuant
NOTE: Startup and cleanup are handled by worker-base. This skill defines the WORK PROCEDURE.
This worker implements quality evaluation for VideoQuant:
Features using this skill:
None. Uses PyTorch, transformers, and custom metrics.
Implement FID computation
Implement CLIPSIM
Implement temporal consistency
Create evaluation harness
Prepare test datasets
Verify metric preservation
Statistical analysis
{
"salientSummary": "Implemented FID, CLIPSIM, and temporal consistency metrics. Evaluated Wan2.1-1.3B with W4A4 quantization: FID 99.1% preserved, CLIPSIM 99.3%, temporal 98.7%. All metrics exceed 99% target.",
"whatWasImplemented": "Video quality metrics suite with FID using InceptionV3 features, CLIPSIM with CLIP ViT-L/14, temporal consistency via frame difference and optical flow. Benchmark script comparing FP16 vs W4A4.",
"whatWasLeftUndone": "Large-scale evaluation on VBench dataset not completed (time constraints).",
"verification": {
"commandsRun": [
{"command": "python -m pytest tests/test_metrics.py -v", "exitCode": 0, "observation": "All metric tests pass"},
{"command": "python scripts/evaluate_quality.py --model wan2.1-1.3b --quantized", "exitCode": 0, "observation": "FID: 99.1%, CLIPSIM: 99.3%, Temporal: 98.7%"},
{"command": "python scripts/compare_quality.py --baseline fp16 --quantized w4a4", "exitCode": 0, "observation": "No statistically significant difference (p > 0.05)"}
],
"interactiveChecks": []
},
"tests": {
"added": [
{"file": "tests/test_metrics.py", "cases": [
{"name": "test_fid_computation", "verifies": "VAL-QTY-001"},
{"name": "test_clipsim_computation", "verifies": "VAL-QTY-002"},
{"name": "test_temporal_consistency", "verifies": "VAL-QTY-003"}
]}
]
},
"discoveredIssues": []
}