Update app.py
Browse files
app.py
CHANGED
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@@ -7,6 +7,7 @@ state_dict = torch.load('fasterRCNNRaccoonRESNET50.pth')
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model.load_state_dict(state_dict)
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size = 384
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infer_tfms = tfms.A.Adapter([*tfms.A.resize_and_pad(size),tfms.A.Normalize()])
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def predict(img):
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# img = PIL.Image.open(img)
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np.int = int
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@@ -15,5 +16,6 @@ def predict(img):
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pred_dict = models.torchvision.faster_rcnn.end2end_detect(img, infer_tfms, model.to("cpu"), class_map=class_map, detection_threshold=0.5)
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return pred_dict['img']
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# Creamos la interfaz y la lanzamos.
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gr.Interface(fn=predict, inputs=["image"], outputs=["image"], examples=['raccoon/train/images/raccoon-197.jpg','raccoon/train/images/raccoon-177.jpg']).launch(share=True,debug=True)
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model.load_state_dict(state_dict)
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size = 384
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infer_tfms = tfms.A.Adapter([*tfms.A.resize_and_pad(size),tfms.A.Normalize()])
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+
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def predict(img):
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# img = PIL.Image.open(img)
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np.int = int
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pred_dict = models.torchvision.faster_rcnn.end2end_detect(img, infer_tfms, model.to("cpu"), class_map=class_map, detection_threshold=0.5)
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return pred_dict['img']
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# Creamos la interfaz y la lanzamos.
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gr.Interface(fn=predict, inputs=["image"], outputs=["image"], examples=['raccoon/train/images/raccoon-197.jpg','raccoon/train/images/raccoon-177.jpg']).launch(share=True,debug=True)
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