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Update app.py
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app.py
CHANGED
@@ -69,7 +69,8 @@ num_anchors = 9
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model = None
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def prepare_model(approach: int):
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global model
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if approach not in [1, 2, 3]:
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raise ValueError("Approach must be 1, 2, or 3.")
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@@ -80,14 +81,24 @@ def prepare_model(approach: int):
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}
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weight_path = os.path.join("model-data", "weights", weight_files[approach])
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if not os.path.exists(weight_path):
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raise FileNotFoundError(f"Weight file not found: {weight_path}")
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input_tensor = Input(shape=(input_shape[0], input_shape[1], 3))
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num_out_filters = (num_anchors // 3) * (5 +
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model = yolo_body(input_tensor, num_out_filters)
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model.load_weights(weight_path)
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@app.on_event("startup")
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def on_startup():
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fix_tf_gpu()
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model = None
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def prepare_model(approach: int):
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global model, anchor_boxes, input_shape, class_names
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if approach not in [1, 2, 3]:
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raise ValueError("Approach must be 1, 2, or 3.")
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}
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weight_path = os.path.join("model-data", "weights", weight_files[approach])
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if not os.path.exists(weight_path):
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raise FileNotFoundError(f"Weight file not found: {weight_path}")
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# Define anchor boxes for YOLO (you may need to adjust these values)
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anchor_boxes = np.array([
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np.array([[10, 13], [16, 30], [33, 23]]) / 32,
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np.array([[30, 61], [62, 45], [59, 119]]) / 16,
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np.array([[116, 90], [156, 198], [373, 326]]) / 8
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], dtype="float64")
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input_tensor = Input(shape=(input_shape[0], input_shape[1], 3))
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num_out_filters = (num_anchors // 3) * (5 + len(class_names))
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model = yolo_body(input_tensor, num_out_filters)
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model.load_weights(weight_path)
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print(f"YOLO model (Approach={approach}) loaded successfully.")
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@app.on_event("startup")
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def on_startup():
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fix_tf_gpu()
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