Create app.py

app.py

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+from icevision.all import *
+import gradio as gr
+
+	
+	# Cargamos el learner
+model = models.torchvision.faster_rcnn.model(backbone=models.torchvision.faster_rcnn.backbones.resnet18_fpn,
+                                             num_classes=2)
+state_dict = torch.load('fasterRCNNkangaroo.pth')
+model.load_state_dict(state_dict)
+	
+	
+	# Definimos una función que se encarga de llevar a cabo las predicciones
+	
+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=ClassMap(['kangaroo']), 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(shape=(128, 128)),examples=['00004.jpg','00014.jpg']).launch(share=False)