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| import gradio as gr | |
| from fastai.vision.all import * | |
| # import os | |
| # Load a pre-trained image classification model | |
| import pathlib | |
| plt = platform.system() | |
| if plt == 'Windows': pathlib.PosixPath = pathlib.WindowsPath | |
| if plt == 'Linux': pathlib.WindowsPath = pathlib.PosixPath | |
| root = os.path.dirname(__file__) | |
| def get_label(fname): | |
| id = int(fname.name[-9:-4]) | |
| # print(id) | |
| cls = int(labels[id-1])-1 | |
| # print(cls) | |
| return name(cls) | |
| learn = load_learner("./models/model.pkl") | |
| # Function to make predictions from an image | |
| def classify_image(image): | |
| # Make a prediction | |
| # Decode the prediction and get the class name | |
| name = learn.predict(image) | |
| return name[0] | |
| # Sample images for user to choose from | |
| sample_images = ["./sample_images/AcuraTLType-S2008.jpg", "./sample_images/AudiR8Coupe2012.jpg","./sample_images/DodgeMagnumWagon2008.jpg"] | |
| iface = gr.Interface( | |
| fn=classify_image, | |
| inputs=gr.Image(label="Select an image", type="filepath"), | |
| outputs="text", | |
| live=False, | |
| title="Clasificador de autos", | |
| description="Sube una imagen para poder clasificar el tipo de auto", | |
| examples=sample_images | |
| ) | |
| iface.launch() |