| from fastai.vision.all import * | |
| import pathlib | |
| import numpy as np | |
| import cv2 | |
| from PIL import image | |
| plt = platform.system() | |
| if plt == 'Linux': pathlib.WindowsPath = pathlib.PosixPath | |
| learn=load_learner("CatvsDogmodel.pkl") | |
| categories=('Cat','Dog') | |
| def classify_image(img): | |
| pred, idx, probs = learn.predict(img) | |
| return dict(zip(categories, map(float,probs))) | |
| import gradio as gr | |
| image=gr.inputs.Image(shape=(224, 224)) | |
| image = cv2.imread(image) | |
| Image.open(image) | |
| image = image/255 | |
| image = np.reshape(image, [1,224,224,3]) | |
| label=gr.outputs.Label() | |
| intf=gr.Interface(fn=classify_image, inputs=image, outputs=label) | |
| intf.launch(inline=False) |