Update app.py

app.py

@@ -5,8 +5,6 @@ from PIL import Image
 import re
 import pandas as pd
 import os
-from datetime import datetime
-import pytz
 
 # --- 1. MODEL LOADING (GLOBAL) ---
 # This part runs only once when the Gradio app starts, making it efficient.
@@ -25,8 +23,6 @@ try:
     print("Model loaded successfully.")
 except Exception as e:
     print(f"Error loading model: {e}")
-    # If the model fails to load, the app is not usable.
-    # We can handle this by raising the exception or setting a flag.
     model = None
     processor = None
 
@@ -36,14 +32,13 @@ def extract_ktp_data(image_files):
     Processes a list of uploaded image files, performs OCR, and extracts structured data.
     
     Args:
-        image_files (list): A list of file-like objects from the Gradio File input.
+        image_files (list): A list of file path objects from the Gradio File input.
 
     Returns:
         pandas.DataFrame: A DataFrame containing the extracted data for each image.
     """
     if not image_files:
         print("No image files provided.")
-        # Return an empty dataframe with the correct columns if no files are uploaded
         return pd.DataFrame(columns=['Filename', 'NIK', 'Nama', 'Tempat Lahir', 'Tanggal Lahir'])
         
     if not model or not processor:
@@ -61,94 +56,70 @@ def extract_ktp_data(image_files):
     }
 
     # Loop through each uploaded file
-    for file_obj in image_files:
-        filename = os.path.basename(file_obj.name)
+    for file_path in image_files:
+        filename = os.path.basename(file_path)
         print(f"-> Processing: {filename}")
         
         try:
-            # Open the image using Pillow
-            image = Image.open(file_obj.name).convert("RGB")
+            image = Image.open(file_path).convert("RGB")
             
-            # Perform inference
             pixel_values = processor(images=image, return_tensors="pt").pixel_values.to(device)
             generated_ids = model.generate(pixel_values, max_length=1024)
             generated_text = processor.batch_decode(generated_ids, skip_special_tokens=True)[0]
             
-            # Store results for the current image
             current_image_data = {"Filename": filename}
             
-            # Apply regex patterns to the OCR output
             for key, pattern in patterns.items():
                 match = re.search(pattern, generated_text)
                 if match:
-                    # Specific capture groups are needed for 'nama' and 'tempat_lahir'
                     if key in ['nama', 'tempat_lahir']:
                         current_image_data[key.replace('_', ' ').title()] = match.group(1).strip()
                     else:
                         current_image_data[key.replace('_', ' ').title()] = match.group(0).strip()
                 else:
-                    # If no match is found, record it as None
                     current_image_data[key.replace('_', ' ').title()] = None
             
             all_results.append(current_image_data)
 
         except Exception as e:
             print(f"Error processing {filename}: {e}")
-            # Add an entry indicating the error for this file
             all_results.append({
-                "Filename": filename, 
-                "NIK": f"Error: {e}", 
-                "Nama": None, 
-                "Tempat Lahir": None, 
-                "Tanggal Lahir": None
+                "Filename": filename, "NIK": f"Error: {e}", "Nama": None, 
+                "Tempat Lahir": None, "Tanggal Lahir": None
             })
 
-    # Convert the list of results into a Pandas DataFrame
     results_df = pd.DataFrame(all_results)
     print("Processing complete.")
     return results_df
 
 # --- 3. UI DEFINITION: THE GRADIO INTERFACE ---
 
-# Get current time in WIB (Western Indonesia Time) for the description
-jakarta_tz = pytz.timezone('Asia/Jakarta')
-current_time_wib = datetime.now(jakarta_tz).strftime("%A, %B %d, %Y at %I:%M %p WIB")
-
-# A description for the app header, written in Markdown
 app_description = f"""
 # KTP (Indonesian ID Card) OCR Extractor 🇮🇩
 This application extracts key information (**NIK, Nama, Tempat Lahir, Tanggal Lahir**) from Indonesian ID cards (KTP). 
 You can upload one or multiple KTP images at once. The results will be displayed in a table below.
 
 *Powered by the `emisilab/model-ocr-ktp-v1` model from Hugging Face.*
-\n*Last Updated: {current_time_wib}*
+\n*Last Updated: Sunday, August 31, 2025 at 12:05 PM WIB (Cilegon)*
 """
 
-# Example images for users to try
 example_images = [
     "https://huggingface.co/emisilab/model-ocr-ktp-v1/resolve/main/ocr-ktp-1.jpg",
     "https://huggingface.co/emisilab/model-ocr-ktp-v1/resolve/main/ocr-ktp-2.jpg"
 ]
 
-# Use gr.Blocks() for a custom layout
 with gr.Blocks(theme=gr.themes.Soft()) as demo:
-    # Title and description
     gr.Markdown(app_description)
 
     with gr.Row():
         with gr.Column(scale=1):
-            # Input component: Allows multiple image uploads
             image_input = gr.File(
                 label="Upload KTP Images",
                 file_count="multiple",
                 file_types=["image"],
-                type="file"
+                type="filepath"  # FIX: Changed 'file' to 'filepath'
             )
-            
-            # Action button to trigger the process
             extract_button = gr.Button("Extract KTP Data", variant="primary")
-            
-            # Add examples for users to easily test the app
             gr.Examples(
                 examples=example_images,
                 inputs=image_input,
@@ -156,13 +127,11 @@ with gr.Blocks(theme=gr.themes.Soft()) as demo:
             )
 
         with gr.Column(scale=2):
-            # Output component: Displays the results in a table
             output_dataframe = gr.DataFrame(
                 label="Extracted Information",
                 headers=['Filename', 'NIK', 'Nama', 'Tempat Lahir', 'Tanggal Lahir']
             )
 
-    # Connect the button to the function
     extract_button.click(
         fn=extract_ktp_data,
         inputs=image_input,
@@ -172,3 +141,4 @@ with gr.Blocks(theme=gr.themes.Soft()) as demo:
 # --- 4. LAUNCH THE APP ---
 if __name__ == "__main__":
     demo.launch()
+