has_end_image

app.py

@@ -643,8 +643,9 @@ def worker_start_end(input_image, end_image, image_position, prompts, n_prompt,
 
         H, W, C = input_image.shape
         height, width = find_nearest_bucket(H, W, resolution=resolution)
+        has_end_image = end_image is not None
         
-        def get_start_latent(input_image, end_image, height, width, vae, gpu, image_encoder, high_vram):
+        def get_start_latent(input_image, has_end_image, end_image, height, width, vae, gpu, image_encoder, high_vram):
             input_image_np = resize_and_center_crop(input_image, target_width=width, target_height=height)
             
             Image.fromarray(input_image_np).save(os.path.join(outputs_folder, f'{job_id}_start.png'))
@@ -653,11 +654,9 @@ def worker_start_end(input_image, end_image, image_position, prompts, n_prompt,
             input_image_pt = input_image_pt.permute(2, 0, 1)[None, :, None]
             
             # Processing end image (if provided)
-            has_end_image = end_image is not None
             if has_end_image:
                 stream.output_queue.push(('progress', (None, '', make_progress_bar_html(0, 'Processing end frame ...'))))
                 
-                H_end, W_end, C_end = end_image.shape
                 end_image_np = resize_and_center_crop(end_image, target_width=width, target_height=height)
                 
                 Image.fromarray(end_image_np).save(os.path.join(outputs_folder, f'{job_id}_end.png'))
@@ -699,7 +698,7 @@ def worker_start_end(input_image, end_image, image_position, prompts, n_prompt,
                 
             return [start_latent, image_encoder_last_hidden_state]
             
-        [start_latent, image_encoder_last_hidden_state] = get_start_latent(input_image, end_image, height, width, vae, gpu, image_encoder, high_vram)
+        [start_latent, image_encoder_last_hidden_state] = get_start_latent(input_image, has_end_image, end_image, height, width, vae, gpu, image_encoder, high_vram)
 
         # Dtype
         image_encoder_last_hidden_state = image_encoder_last_hidden_state.to(transformer.dtype)