Show dataset YOLO training curves
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@@ -44,7 +44,11 @@ def evaluate_project() -> dict:
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"upload_ui": "uploadDatasetFiles" in frontend_text and "labels" in frontend_text and "masks" in frontend_text,
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"dataset_quality_ui": "DatasetQuality" in frontend_text and "generateSelectedYoloYaml" in frontend_text,
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"uploaded_yolo_workflow_ui": "startSelectedYoloTrain" in frontend_text and "startSelectedYoloPredict" in frontend_text and "startSelectedYoloHeatmap" in frontend_text,
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"dataset_yolo_outputs_ui": "DatasetYoloOutputs" in frontend_text and "selectedYoloOutputs" in frontend_text and "BEST.PT READY" in frontend_text,
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"dataset_yolo_outputs_ui": "DatasetYoloOutputs" in frontend_text
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and "selectedYoloOutputs" in frontend_text
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and "BEST.PT READY" in frontend_text
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and "datasetOutputCurve" in frontend_text
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and "MiniCurvePlot" in frontend_text,
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"loss_result_ui": "loss" in frontend_text.lower() and "heatmap" in frontend_text.lower() and "CurvePanel" in frontend_text,
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"job_progress_ui": "JobProgressBar" in frontend_text and "progressTrack" in frontend_text,
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"runtime_readiness_ui": "runtimeReadiness" in frontend_text and "环境就绪" in frontend_text,
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@@ -216,8 +216,8 @@ def api_results() -> list[dict]:
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@app.get("/api/results/curves")
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def api_result_curves() -> list[dict]:
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return scan_training_curves()
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def api_result_curves(limit: int = 100) -> list[dict]:
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return scan_training_curves(limit=limit)
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@app.get("/api/artifacts/{artifact_path:path}")
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