Update app.py

app.py

@@ -2,19 +2,26 @@ import gradio as gr
 from fastai.vision.all import *
 import skimage
 from fastai.vision.all import PILImage
+import datetime  # Import datetime to generate unique filenames
 
 learn = load_learner('export.pkl')
 
 labels = learn.dls.vocab
 
-
 def predict(img):
- img = PILImage.create(img)
- img = img.resize((512, 512))
- pred,pred_idx,probs = learn.predict(img)
- return {labels[i]: float(probs[i]) for i in range(len(labels))}
+    img = PILImage.create(img)
+    img = img.resize((512, 512))
+    pred, pred_idx, probs = learn.predict(img)
+    
+    # Check if the prediction is "elephant"
+    if pred == "elephant":
+        # Generate a unique filename using the current timestamp
+        filename = f"elephant_{datetime.datetime.now().strftime('%Y%m%d_%H%M%S')}.jpg"
+        # Save the image
+        img.save(filename)
+    
+    return {labels[i]: float(probs[i]) for i in range(len(labels))}
 
 examples = ['image1.jpg', 'image2.jpg']
 
 gr.Interface(fn=predict, inputs=gr.components.Image(), outputs=gr.components.Label(num_top_classes=3), examples=examples).launch()
-