|
import icevision |
|
from icevision.all import * |
|
import torch |
|
import gradio as gr |
|
import PIL |
|
from PIL import Image |
|
|
|
|
|
learner = torch.load('fasterRCNNKangaroo_obligatorio.pth',map_location='cpu') |
|
|
|
|
|
def predict(img): |
|
|
|
size = 384 |
|
class_map = ClassMap(['kangaroo']) |
|
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, learner.to("cpu"), class_map=class_map, detection_threshold=0.5) |
|
|
|
return img |
|
|
|
|
|
gr.Interface(fn=predict, inputs=gr.inputs.Image(shape=(128, 128)), outputs=gr.outputs.Image(type="pil",label='Imagen resultado'),examples=['00001.jpg','00002.jpg']).launch(share=False) |
|
|