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app.py

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+from fastai.vision.all import *
+from icevision.all import * 
+import gradio as gr
+
+
+class_map = ClassMap(['raccoon'])
+model = models.torchvision.faster_rcnn.model(backbone=models.torchvision.faster_rcnn.backbones.resnet18_fpn(pretrained=True),num_classes=len(class_map))
+state_dict = torch.load('fasterRCNNraccoon.pth',map_location=torch.device('cpu'))
+model.load_state_dict(state_dict)
+
+infer_tfms = tfms.A.Adapter([*tfms.A.resize_and_pad(384),tfms.A.Normalize()])
+
+def predict(img):
+  img = PILImage.create(img)
+  pred_dict  = models.torchvision.faster_rcnn.end2end_detect(img, infer_tfms, model.to("cpu"), class_map=class_map, detection_threshold=0.5)
+  return pred_dict['img']
+
+   
+# Creamos la interfaz y la lanzamos. 
+gr.Interface(fn=predict, inputs=gr.inputs.Image(shape=(128, 128)), outputs=gr.outputs.Image(),examples=['raccoon-101.jpg','raccoon-102.jpg']).launch(share=False)
+ 

fasterRCNNraccoon.pth

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+version https://git-lfs.github.com/spec/v1
+oid sha256:e6996a725f6a6c74d837297075983a566f90eb8526123f80eb2e2b6962f4c987
+size 113220709