Spaces:
Running
on
Zero
Running
on
Zero
Martin Tomov
commited on
BGR color code issue
Browse files
app.py
CHANGED
@@ -151,7 +151,7 @@ def extract_and_paste_insect(original_image: np.ndarray, detection: DetectionRes
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background[y_offset:y_end, x_offset:x_end] = insect
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def create_yellow_background_with_insects(image: np.ndarray, detections: List[DetectionResult]) -> np.ndarray:
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yellow_background = np.full((image.shape[0], image.shape[1], 3), (0, 255, 255), dtype=np.uint8)
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for detection in detections:
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if detection.mask is not None:
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extract_and_paste_insect(image, detection, yellow_background)
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@@ -191,28 +191,18 @@ def detections_to_json(detections):
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detections_list.append(detection_dict)
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return detections_list
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def process_image(image, include_json
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labels = ["insect"]
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original_image, detections = grounded_segmentation(image, labels, threshold=0.3, polygon_refinement=True)
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yellow_background_with_insects = create_yellow_background_with_insects(np.array(original_image), detections)
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output1 = yellow_background_with_insects
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output2 = None
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output3 = None
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output4 = None
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if include_json:
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detections_json = detections_to_json(detections)
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json_output_path = "insect_detections.json"
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with open(json_output_path, 'w') as json_file:
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json.dump(detections_json, json_file, indent=4)
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output3 = original_image
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output4 = detections
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return output1, output2, output3, output4
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examples = [
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["flower-night.jpg"]
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@@ -220,8 +210,8 @@ examples = [
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gr.Interface(
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fn=process_image,
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inputs=[gr.Image(type="pil"), gr.Checkbox(label="Include JSON", value=False)
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outputs=[gr.Image(type="numpy"), gr.Textbox()
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title="InsectSAM π",
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examples=examples
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).launch()
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background[y_offset:y_end, x_offset:x_end] = insect
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def create_yellow_background_with_insects(image: np.ndarray, detections: List[DetectionResult]) -> np.ndarray:
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yellow_background = np.full((image.shape[0], image.shape[1], 3), (0, 255, 255), dtype=np.uint8) # BGR for yellow
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for detection in detections:
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if detection.mask is not None:
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extract_and_paste_insect(image, detection, yellow_background)
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detections_list.append(detection_dict)
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return detections_list
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+
def process_image(image, include_json):
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labels = ["insect"]
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original_image, detections = grounded_segmentation(image, labels, threshold=0.3, polygon_refinement=True)
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yellow_background_with_insects = create_yellow_background_with_insects(np.array(original_image), detections)
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if include_json:
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detections_json = detections_to_json(detections)
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json_output_path = "insect_detections.json"
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with open(json_output_path, 'w') as json_file:
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json.dump(detections_json, json_file, indent=4)
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return yellow_background_with_insects, json.dumps(detections_json, separators=(',', ':'))
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else:
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return yellow_background_with_insects, None
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examples = [
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["flower-night.jpg"]
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gr.Interface(
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fn=process_image,
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inputs=[gr.Image(type="pil"), gr.Checkbox(label="Include JSON", value=False)],
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outputs=[gr.Image(type="numpy"), gr.Textbox()],
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title="InsectSAM π",
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examples=examples
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).launch()
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