Update app.py

app.py

@@ -5,6 +5,7 @@ import requests
 from io import BytesIO
 import threading
 import time
+import json
 
 # Load models and processor only once using session state
 if 'models_loaded' not in st.session_state:
@@ -51,12 +52,17 @@ def pipes(imagepath):
     encoding, image = imageprocessing(imagepath)
     # Using threading for faster results
     results = [None] * 4
+
+    def update_results(index, func):
+        results[index] = func(encoding)
+
     threads = [
-        threading.Thread(target=lambda: results.__setitem__(0, topwear(encoding))),
-        threading.Thread(target=lambda: results.__setitem__(1, patterns(encoding))),
-        threading.Thread(target=lambda: results.__setitem__(2, prints(encoding))),
-        threading.Thread(target=lambda: results.__setitem__(3, sleevelengths(encoding))),
+        threading.Thread(target=update_results, args=(0, topwear)),
+        threading.Thread(target=update_results, args=(1, patterns)),
+        threading.Thread(target=update_results, args=(2, prints)),
+        threading.Thread(target=update_results, args=(3, sleevelengths)),
     ]
+
     for thread in threads:
         thread.start()
     for thread in threads:
@@ -75,11 +81,8 @@ if image_url:
     results, img = pipes(image_url)
     st.image(img.resize((200, 200)), caption="Uploaded Image", use_column_width=False)
     
-    # Display results
-    st.write("Classification Results:")
-    st.write(f"Topwear: {results['top']}")
-    st.write(f"Pattern: {results['pattern']}")
-    st.write(f"Print: {results['print']}")
-    st.write(f"Sleeve Length: {results['sleeve_length']}")
+    # Display results as JSON
+    st.write("Classification Results (JSON):")
+    st.json(results)  # Output as JSON
     
     st.write(f"Time taken: {time.time() - start_time:.2f} seconds")