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from icevision.all import *
import gradio as gr
state_dict = roch.load('fasterRCNNKangaroo.pth')
model.load_state_dict(state_dict)
labels = learn.dls.vocab
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.Label(num_top_classes=3),examples=['00001.jpg','00002.jpg']).launch(share=False) |