| from icevision.all import * | |
| import gradio as gr | |
| class_map = ClassMap(['kangaroo']) | |
| model = models.torchvision.faster_rcnn.model(backbone=models.torchvision.faster_rcnn.backbones.resnet18_fpn, num_classes=len(class_map)) | |
| state_dict = torch.load('fasterRCNNKangaroo.pth') | |
| model.load_state_dict(state_dict) | |
| size = 384 | |
| def predict(img): | |
| img = PILImage.create(img) | |
| infer_tfms = tfms.A.Adapter([*tfms.A.resize_and_pad(size),tfms.A.Normalize()]) | |
| 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 | |
| gr.Interface(fn=predict, inputs=gr.inputs.Image(shape=(128,128)), outputs=gr.outputs.Image(shape=(128,128)),examples=['00001.jpg','00002.jpg']).launch(share=False) |