Update app.py

app.py

@@ -1,24 +1,55 @@
 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('mindwrapped/pokemon-card-checker')
 
 def check_card(img):
     pred_label, _, scores = learn.predict(img)
     scores = scores.detach().numpy()
-    return {'real': float(scores[1]), 'fake': float(scores[0])}
+    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=['fake', 'real'],
+      num_samples=100,
+      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",
+  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='A resnet34 model fine-tuned to determine whether Pokemon cards are real or fake. \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\n![visitor badge](https://visitor-badge.glitch.me/badge?page_id=mindwrapped.pokemon-card-checker-space)',
+  description='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. \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 :D \n\n([View Labels](https://gist.github.com/mindwrapped/e5aad747757ef006037a1a1982be34fc)) \n\n![visitor badge](https://visitor-badge.glitch.me/badge?page_id=mindwrapped.pokemon-card-checker-space)',
   live=False,
   )
 
-demo.launch()
+demo.launch(debug=True)