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https://huggingface.co/spaces/igmarco/Practica2/resolve/main/app.py
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1.92 kB
| from huggingface_hub import from_pretrained_fastai | |
| import gradio as gr | |
| from fastai.vision.all import * | |
| from icevision.all import * | |
| import PIL | |
| class_map = ['raccoon'] | |
| presize = 512 | |
| size = 384 | |
| train_tfms = tfms.A.Adapter( | |
| [*tfms.A.aug_tfms(size=size, presize=presize), tfms.A.Normalize()] | |
| ) | |
| valid_tfms = tfms.A.Adapter([*tfms.A.resize_and_pad(size), tfms.A.Normalize()]) | |
| model1 = models.torchvision.faster_rcnn.model(backbone=models.torchvision.faster_rcnn.backbones.resnet18_fpn(pretrained=True), num_classes=len(class_map)+1) | |
| state_dict = torch.load('fasterRCNN_resnet18_Raccoons.pth', map_location=torch.device('cpu')) | |
| model1.load_state_dict(state_dict) | |
| def show_preds(input_image, display_label, display_bbox, detection_threshold): | |
| if detection_threshold==0: detection_threshold=0.5 | |
| img = PIL.Image.fromarray(input_image, 'RGB') | |
| pred_dict = models.torchvision.faster_rcnn.end2end_detect(img, valid_tfms, model1, class_map=ClassMap(class_map), detection_threshold=detection_threshold, | |
| display_label=display_label, display_bbox=display_bbox, return_img=True, | |
| font_size=16, label_color="#FF59D6") | |
| return pred_dict['img'] | |
| # display_chkbox = gr.inputs.CheckboxGroup(["Label", "BBox"], label="Display", default=True) | |
| display_chkbox_label = gr.inputs.Checkbox(label="Label", default=True) | |
| display_chkbox_box = gr.inputs.Checkbox(label="Box", default=True) | |
| detection_threshold_slider = gr.inputs.Slider(minimum=0, maximum=1, step=0.1, default=0.5, label="Detection Threshold") | |
| outputs = gr.outputs.Image(type="pil") | |
| 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]]) | |
| gr_interface.launch(inline=False, share=False, debug=True) |