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Running
Running
Orkhan Hasanli commited on
Commit ·
5ce2fb0
1
Parent(s): f851934
Modified default thresholds for display and gap
Browse files
app.py
CHANGED
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@@ -108,7 +108,7 @@ def run_detection(image, model):
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return out_img, det_json
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def run_dfine_classify(image, refs_path, dfine_threshold, dfine_model_choice, min_display_conf=0.
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"""Tab 2: D-FINE first, then classify crops with Jina.
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Returns (group_crop_gallery, known_crop_gallery, status_message).
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"""
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@@ -232,7 +232,9 @@ with gr.Blocks(title="Small Object Detection") as app:
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"**D-FINE** runs first (person/car grouping), then small-object crops are classified with **Jina**. "
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"Choose D-FINE model size (Medium or Large). "
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"Uses the **refs** folder (one subfolder per class, e.g. refs/phone/, refs/cigarette/) "
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"with reference images."
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)
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with gr.Row():
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@@ -285,7 +287,7 @@ with gr.Blocks(title="Small Object Detection") as app:
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threshold_slider = gr.Slider(
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minimum=0.0,
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maximum=1.0,
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value=0.
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step=0.005,
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label="Threshold (min display confidence)",
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)
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@@ -293,9 +295,9 @@ with gr.Blocks(title="Small Object Detection") as app:
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gap_slider = gr.Slider(
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minimum=0.0,
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maximum=0.02,
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value=0.
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step=0.001,
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label="Gap
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)
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out_gallery_dfine = gr.Gallery(
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return out_img, det_json
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+
def run_dfine_classify(image, refs_path, dfine_threshold, dfine_model_choice, min_display_conf=0.703, gap_threshold=0.005):
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"""Tab 2: D-FINE first, then classify crops with Jina.
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Returns (group_crop_gallery, known_crop_gallery, status_message).
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"""
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"**D-FINE** runs first (person/car grouping), then small-object crops are classified with **Jina**. "
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"Choose D-FINE model size (Medium or Large). "
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"Uses the **refs** folder (one subfolder per class, e.g. refs/phone/, refs/cigarette/) "
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"with reference images.\n\n"
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"**Gap** = how much the top class (e.g. gun) must beat the next-best class (e.g. phone). "
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"Bigger gap means the model is more sure; we only accept the label if both confidence and gap are high enough."
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)
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with gr.Row():
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threshold_slider = gr.Slider(
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minimum=0.0,
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maximum=1.0,
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value=0.703,
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step=0.005,
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label="Threshold (min display confidence)",
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)
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gap_slider = gr.Slider(
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minimum=0.0,
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maximum=0.02,
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value=0.005,
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step=0.001,
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label="Gap: how much the top guess must beat the runner-up (higher = stricter, fewer accepted)",
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)
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out_gallery_dfine = gr.Gallery(
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