Update app.py

app.py

@@ -38,19 +38,25 @@ def remove_background_bria(input_path):
 
 # Fungsi untuk memproses gambar menggunakan prompt
 def text_to_image(prompt):
-    os.makedirs("generated_images", exist_ok=True)
-    image = sd_model(prompt).images[0]  # Use sd_model instead of pipe
+    os.makedirs("generated_images", exist_ok=True)  # Ensure the directory exists
+    image = sd_model(prompt).images[0]  # Generate image using the model
+    # Create a sanitized filename by replacing spaces with underscores
     image_path = f"generated_images/{prompt.replace(' ', '_')}.png"
-    image.save(image_path)
-    return image, image_path
-
-def text_image_to_image(image, prompt):
-    os.makedirs("generated_images", exist_ok=True)
-    # Convert input image to PIL Image for processing
-    modified_image = sd_model(prompt, init_image=image, strength=0.75).images[0]  # Use sd_model here too
+    image.save(image_path)  # Save the generated image
+    return image, image_path  # Return the image and its path
+
+# Function to modify an image based on a text prompt
+def text_image_to_image(input_image, prompt):
+    os.makedirs("generated_images", exist_ok=True)  # Ensure the directory exists
+    # Convert input image to PIL Image if necessary
+    if not isinstance(input_image, Image.Image):
+        input_image = Image.open(input_image)  # Load image from path if given as string
+    # Generate modified image using the model with the input image and prompt
+    modified_image = sd_model(prompt, init_image=input_image, strength=0.75).images[0]
+    # Create a sanitized filename for the modified image
     image_path = f"generated_images/{prompt.replace(' ', '_')}_modified.png"
-    modified_image.save(image_path)
-    return modified_image, image_path
+    modified_image.save(image_path)  # Save the modified image
+    return modified_image, image_path  # Return the modified image and its path
 
 def get_bounding_box_with_threshold(image, threshold):
     # Convert image to numpy array
@@ -509,10 +515,19 @@ def process_images(input_files, bg_method='rembg', watermark_path=None, canvas_s
     
     # Create a zip file of processed images
     with zipfile.ZipFile(output_zip_path, 'w') as zipf:
-        for processed_img in processed_images:
-            zipf.write(processed_img)
-    
-    return processed_images, output_zip_path
+        for file_info in processed_images:
+            file_path, _ = file_info
+            zipf.write(file_path, os.path.basename(file_path))
+
+    with open(os.path.join(output_folder, 'process_log.json'), 'w') as log_file:
+        json.dump(all_logs, log_file, indent=4)
+    print("Comprehensive log saved to", os.path.join(output_folder, 'process_log.json'))
+
+    end_time = time.time()
+    processing_time = end_time - start_time
+    print(f"Processing time: {processing_time} seconds")
+
+    return original_images, processed_images, output_zip_path, processing_time
 
 def gradio_interface(input_files, bg_method, watermark, canvas_size, output_format, bg_choice, custom_color, num_workers):
     progress = gr.Progress()