Update app.py

app.py

@@ -1,33 +1,12 @@
 import gradio as gr
 from fastai.vision.all import load_learner, PILImage
 import os
-from pathlib import Path
 import pathlib
 
 if os.name == "nt":  # Windows
     pathlib.PosixPath = pathlib.WindowsPath
 
-model_path = os.path.join(os.getcwd(), "cards_classification.pkl")
-print(f"model path: {model_path}")
-
-# Debug: Print current working directory and list files
-print(f"Current working directory: {os.getcwd()}")
-print(f"Files in current directory: {os.listdir('.')}")
-
-# Check if test_images directory exists
-if os.path.exists('test_images'):
-    print(f"test_images directory found!")
-    print(f"Files in test_images: {os.listdir('test_images')}")
-else:
-    print(f"test_images directory NOT found!")
-    # Check home directory
-    home_app = '/home/user/app'
-    if os.path.exists(home_app):
-        print(f"Files in {home_app}: {os.listdir(home_app)}")
-        if os.path.exists(os.path.join(home_app, 'test_images')):
-            print(f"Files in {home_app}/test_images: {os.listdir(os.path.join(home_app, 'test_images'))}")
-
-learn = load_learner(model_path, cpu=True)
+learn = load_learner("cards_classification.pkl", cpu=True)
 
 def classify_image(image):
     if image is None:
@@ -36,25 +15,11 @@ def classify_image(image):
     pred_class, pred_idx, probs = learn.predict(img)
     return {learn.dls.vocab[i]: float(probs[i]) for i in range(len(probs))}
 
-CARDS = ['ace of clubs', 'ace of diamonds', 'ace of hearts', 'ace of spades', 
-         'eight of clubs', 'eight of diamonds', 'eight of hearts', 'eight of spades', 
-         'five of clubs', 'five of diamonds', 'five of hearts', 'five of spades', 
-         'four of clubs', 'four of diamonds', 'four of hearts', 'four of spades', 
-         'jack of clubs', 'jack of diamonds', 'jack of hearts', 'jack of spades', 
-         'joker', 'king of clubs', 'king of diamonds', 'king of hearts', 'king of spades', 
-         'nine of clubs', 'nine of diamonds', 'nine of hearts', 'nine of spades', 
-         'queen of clubs', 'queen of diamonds', 'queen of hearts', 'queen of spades', 
-         'seven of clubs', 'seven of diamonds', 'seven of hearts', 'seven of spades', 
-         'six of clubs', 'six of diamonds', 'six of hearts', 'six of spades', 
-         'ten of clubs', 'ten of diamonds', 'ten of hearts', 'ten of spades', 
-         'three of clubs', 'three of diamonds', 'three of hearts', 'three of spades', 
-         'two of clubs', 'two of diamonds', 'two of hearts', 'two of spades']
-
-# Create the interface with detailed description
+# Create the interface
 with gr.Blocks() as iface:
     gr.Markdown(
         """
-        🃏 Playing Card Image Classifier
+        # 🃏 Playing Card Image Classifier
         
         This AI model can recognize and classify images of standard playing cards using deep learning.
         
@@ -68,7 +33,6 @@ with gr.Blocks() as iface:
         - Joker card (In total: 53 classes)
         
         ### Tips for best results:
-        - Use clear, high-resolution images
         - Make sure the card is fully visible
         - Avoid heavy glare, blur, or occlusion
         - One card per image works best
@@ -82,39 +46,17 @@ with gr.Blocks() as iface:
         with gr.Column():
             output_label = gr.Label(num_top_classes=3, label="Predictions")
     
-    # Use absolute paths or check which path works
-    example_paths = []
-    test_dir = "test_images"
-    
-    # Try to find the correct path
-    if os.path.exists(test_dir):
-        base_path = test_dir
-    elif os.path.exists("/home/user/app/test_images"):
-        base_path = "/home/user/app/test_images"
-    else:
-        base_path = None
-        print("WARNING: Could not find test_images directory!")
-    
-    if base_path:
-        example_files = ["king_of_diamonds.jpg", "jack_of_spades.jpg", 
-                        "ace_of_diamonds.jpg", "three_of_hearts.jpg", "ace_of_spades.jpg"]
-        
-        for filename in example_files:
-            full_path = os.path.join(base_path, filename)
-            if os.path.exists(full_path):
-                example_paths.append([full_path])
-                print(f"Found example: {full_path}")
-            else:
-                print(f"Missing example: {full_path}")
-    
-    if example_paths:
-        gr.Examples(
-            examples=example_paths,
-            inputs=input_image,
-            label="Try an example"
-        )
-    else:
-        gr.Markdown("⚠️ Example images not found. Please upload your own image.")
+    gr.Examples(
+        examples=[
+            ["test_images/king_of_diamonds.jpg"],
+            ["test_images/jack_of_spades.jpg"],
+            ["test_images/ace_of_diamonds.jpg"],
+            ["test_images/three_of_hearts.jpg"],
+            ["test_images/ace_of_spades.jpg"]
+        ],
+        inputs=input_image,
+        label="Try an example"
+    )
     
     submit_btn.click(fn=classify_image, inputs=input_image, outputs=output_label)