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| import numpy as np | |
| import gradio as gr | |
| from huggingface_hub import from_pretrained_fastai | |
| from lime import lime_image | |
| from skimage.segmentation import mark_boundaries | |
| learn = from_pretrained_fastai('hugginglearners/pokemon-card-checker') | |
| def check_card(img): | |
| pred_label, _, scores = learn.predict(img) | |
| scores = scores.detach().numpy() | |
| scores = {'real': float(scores[1]), 'fake': float(scores[0])} | |
| print(np.array(img).shape) | |
| # Lime Explanation | |
| explainer = lime_image.LimeImageExplainer() | |
| explanation = explainer.explain_instance( | |
| np.array(img), | |
| classifier_fn=classify_cards, | |
| labels=['0', '1'], | |
| num_samples=1000, | |
| random_seed=42, | |
| ) | |
| temp, mask = explanation.get_image_and_mask(explanation.top_labels[0], positive_only=False, num_features=10, hide_rest=False) | |
| img_boundry = mark_boundaries(temp/255.0, mask) | |
| return scores, img_boundry | |
| def classify_cards(imgs): | |
| print(imgs.shape) | |
| scores = [] | |
| for i in range(imgs.shape[0]): | |
| pred_label, _, score = learn.predict(imgs[i]) | |
| scores.append(score.detach().numpy()) | |
| scores = np.array(scores) | |
| print(scores.shape) | |
| return scores | |
| demo = gr.Interface( | |
| fn=check_card, | |
| inputs='image', | |
| outputs=["label", "image"], | |
| examples=['real-1.jpeg','real-2.jpeg','fake-1.jpeg','fake-2.jpeg','real-3.jpeg','real-4.jpeg','fake-3.jpeg','fake-4.jpeg'], | |
| title='Pokemon Card Checker', | |
| description='This space uses a resnet34 model fine-tuned to determine whether Pokemon cards are real or fake. \n\nAdded [LIME](https://github.com/marcotcr/lime) to show what contributed to the predicted label (green shows what contributed towards that label and red shows what contributed against the label predicted).\n\n[Dataset](https://www.kaggle.com/datasets/ongshujian/real-and-fake-pokemon-cards) created by [Shujian Ong](https://www.kaggle.com/ongshujian).', | |
| article='Can you guess which cards are real and fake? \n\nI can\'t 🤔 \n\n([View Labels](https://gist.github.com/mindwrapped/e5aad747757ef006037a1a1982be34fc)) \n\nSpace and model by Scott Krstyen (mindwrapped) \n\n', | |
| live=False, | |
| ) | |
| demo.launch(debug=True) |