|
from fastai.vision.all import * |
|
from icevision.all import * |
|
from fastai.basics import * |
|
from fastai.callback import * |
|
from icevision import models |
|
import PIL |
|
import gradio as gr |
|
|
|
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) |
|
|
|
|
|
|
|
|
|
infer_tfms = tfms.A.Adapter([*tfms.A.resize_and_pad(384),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=['00004.jpg','00014.jpg']).launch(share=False) |
