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Update app.py
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app.py
CHANGED
@@ -30,30 +30,29 @@ cfg.MODEL.ROI_HEADS.SCORE_THRESH_TEST = 0.5
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cfg.MODEL.WEIGHTS = "model_weights/chatswood_buildings_poc.pth"
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cfg.MODEL.ROI_HEADS.NUM_CLASSES = 8
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def segment_buildings(
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im = cv2.imread(input_image)
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outputs = predictor(im)
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v = Visualizer(im[:, :, ::-1], MetadataCatalog.get(cfg.DATASETS.TRAIN[0]), scale=1.2)
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out = v.draw_instance_predictions(outputs["instances"].to("cpu"))
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return Image.fromarray(np.uint8(out.get_image())).convert('RGB')
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# gradio components
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gr_image_input = gr.inputs.Image(type="pil")
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"""
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gr_slider_confidence = gr.inputs.Slider(0,1,.1,.7,
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label='Set confidence threshold % for masks')
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"""
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# gradio outputs
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title = "Building Segmentation"
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description = "An instance segmentation demo for identifying boundaries of buildings in aerial images using DETR (End-to-End Object Detection) model with MaskRCNN-101 backbone"
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# Create user interface and launch
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gr.Interface(segment_buildings,
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inputs =
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outputs =
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title = title,
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enable_queue = True,
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description = description).launch()
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cfg.MODEL.WEIGHTS = "model_weights/chatswood_buildings_poc.pth"
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cfg.MODEL.ROI_HEADS.NUM_CLASSES = 8
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def segment_buildings(im):
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outputs = predictor(im)
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v = Visualizer(im[:, :, ::-1], MetadataCatalog.get(cfg.DATASETS.TRAIN[0]), scale=1.2)
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out = v.draw_instance_predictions(outputs["instances"].to("cpu"))
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return Image.fromarray(np.uint8(out.get_image())).convert('RGB')
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# gradio components
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"""
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gr_slider_confidence = gr.inputs.Slider(0,1,.1,.7,
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label='Set confidence threshold % for masks')
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"""
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# gradio outputs
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inputs = gr.inputs.Image(type="pil", label="Input Image")
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outputs = gr.outputs.Image(type="pil", label="Output Image")
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title = "Building Segmentation"
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description = "An instance segmentation demo for identifying boundaries of buildings in aerial images using DETR (End-to-End Object Detection) model with MaskRCNN-101 backbone"
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# Create user interface and launch
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gr.Interface(segment_buildings,
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inputs = inputs,
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outputs = outputs,
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title = title,
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enable_queue = True,
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description = description).launch()
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