| from fastai.vision.all import * |
| from icevision.all import * |
| from fastai.basics import * |
| from fastai.callback import * |
| from icevision import models |
| import gradio as gr |
| import PIL |
|
|
|
|
| class_map = ClassMap(['kangaroo']) |
| model = models.torchvision.faster_rcnn.model(backbone=models.torchvision.faster_rcnn.backbones.resnet18_fpn(pretrained=True), num_classes=len(class_map)) |
| state_dict = torch.load('fasterRCNNKangaroo.pth', map_location=torch.device('cpu')) |
| model.load_state_dict(state_dict) |
| size = 384 |
|
|
| infer_tfms = tfms.A.Adapter([*tfms.A.resize_and_pad(size),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=class_map, detection_threshold=0.5) |
| return pred_dict['img'] |
| |
| gr.Interface(fn=predict, inputs=gr.inputs.Image(shape=(128,128)), outputs=gr.outputs.Image(),examples=['00001.jpg','00002.jpg']).launch(share=False) |
