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from fastai.vision.all import * |
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from icevision.all import * |
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import gradio as gr |
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class_map = ClassMap(['raccoon']) |
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model = models.torchvision.faster_rcnn.model(backbone=models.torchvision.faster_rcnn.backbones.resnet18_fpn(pretrained=True),num_classes=len(class_map)) |
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state_dict = torch.load('fasterRCNNraccoon.pth',map_location=torch.device('cpu')) |
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model.load_state_dict(state_dict) |
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infer_tfms = tfms.A.Adapter([*tfms.A.resize_and_pad(384),tfms.A.Normalize()]) |
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def predict(img): |
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img = PILImage.create(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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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) |
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