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| import gradio as gr | |
| import os | |
| from core.predict import ImageClassifier | |
| from PIL import Image | |
| cwd = os.getcwd() | |
| model_path = os.path.join(cwd, "model", "cnn_model.pth") | |
| classifier = ImageClassifier(model_path=model_path, class_names={0: 'person', 1: 'Dog', 2: 'Cat'}) | |
| def classify_image(image): | |
| image_path = "uploaded_image.jpg" | |
| image.save(image_path) | |
| label, output_path = classifier.predict(image_path) | |
| return label, Image.open(output_path) | |
| demo = gr.Interface( | |
| fn=classify_image, | |
| inputs=gr.Image(type="pil"), | |
| outputs=[gr.Textbox(label = "Prediction"), gr.Image(label = "Labelled Image")], | |
| title = " Image Classification app ", | |
| description = " Upload an image to classify as Cat, Dog or Person " | |
| ) | |
| if __name__ == "__main__": | |
| demo.launch() |