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from huggingface_hub import from_pretrained_fastai |
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import gradio as gr |
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from fastai.vision.all import * |
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from icevision.all import * |
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import PIL |
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class_map = ['raccoon'] |
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presize = 512 |
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size = 384 |
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train_tfms = tfms.A.Adapter( |
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[*tfms.A.aug_tfms(size=size, presize=presize), tfms.A.Normalize()] |
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) |
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valid_tfms = tfms.A.Adapter([*tfms.A.resize_and_pad(size), tfms.A.Normalize()]) |
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model1 = models.torchvision.faster_rcnn.model(backbone=models.torchvision.faster_rcnn.backbones.resnet18_fpn(pretrained=True), num_classes=len(class_map)+1) |
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state_dict = torch.load('fasterRCNN_resnet18_Raccoons.pth', map_location=torch.device('cpu')) |
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model1.load_state_dict(state_dict) |
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def show_preds(input_image, display_label, display_bbox, detection_threshold): |
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if detection_threshold==0: detection_threshold=0.5 |
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img = PIL.Image.fromarray(input_image, 'RGB') |
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pred_dict = models.torchvision.faster_rcnn.end2end_detect(img, valid_tfms, model1, class_map=ClassMap(class_map), detection_threshold=detection_threshold, |
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display_label=display_label, display_bbox=display_bbox, return_img=True, |
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font_size=16, label_color="#FF59D6") |
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return pred_dict['img'] |
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display_chkbox_label = gr.inputs.Checkbox(label="Label", default=True) |
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display_chkbox_box = gr.inputs.Checkbox(label="Box", default=True) |
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detection_threshold_slider = gr.inputs.Slider(minimum=0, maximum=1, step=0.1, default=0.5, label="Detection Threshold") |
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outputs = gr.outputs.Image(type="pil") |
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gr_interface = gr.Interface(fn=show_preds, inputs=["image", display_chkbox_label, display_chkbox_box, detection_threshold_slider], outputs=outputs, examples=[['raccoon1.jpg', True, True, 0.5], ['raccoon2.jpg', True, True, 0.5]]) |
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gr_interface.launch(inline=False, share=False, debug=True) |
