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Update app.py
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app.py
CHANGED
@@ -19,7 +19,7 @@ category_index = label_map_util.create_category_index_from_labelmap(PATH_TO_LABE
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def pil_image_as_numpy_array(pilimg):
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img_array = tf.keras.utils.img_to_array(pilimg)
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img_array = np.expand_dims(img_array, axis=0)
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return img_array
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@@ -53,13 +53,10 @@ def predict(pilimg):
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def predict2(image_np):
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results = detection_model(image_np)
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# different object detection models have additional results
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result = {key:value.numpy() for key,value in results.items()}
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label_id_offset = 0
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image_np_with_detections = image_np.copy()
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viz_utils.visualize_boxes_and_labels_on_image_array(
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image_np_with_detections[0],
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result['detection_boxes'][0],
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@@ -71,7 +68,6 @@ def predict2(image_np):
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min_score_thresh=0.50,
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agnostic_mode=False,
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line_thickness=3)
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result_pil_img = tf.keras.utils.array_to_img(image_np_with_detections[0])
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return result_pil_img
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def pil_image_as_numpy_array(pilimg):
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+
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img_array = tf.keras.utils.img_to_array(pilimg)
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img_array = np.expand_dims(img_array, axis=0)
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return img_array
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def predict2(image_np):
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results = detection_model(image_np)
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# different object detection models have additional results
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result = {key:value.numpy() for key,value in results.items()}
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label_id_offset = 0
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image_np_with_detections = image_np.copy()
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viz_utils.visualize_boxes_and_labels_on_image_array(
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image_np_with_detections[0],
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result['detection_boxes'][0],
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min_score_thresh=0.50,
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agnostic_mode=False,
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line_thickness=3)
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result_pil_img = tf.keras.utils.array_to_img(image_np_with_detections[0])
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return result_pil_img
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