Update app.py

app.py

@@ -39,6 +39,7 @@ def generate_an_image_from_text(text, text_size_, width, lenght):
     # font def 
     font_dir = ''
     # Get a list of all the font files in the directory
+    print("start generation")
     font_files = glob.glob(os.path.join(dir_path, 'fonts', '*.ttf'))
     # Get a list of font paths
     font_paths = []
@@ -55,22 +56,30 @@ def generate_an_image_from_text(text, text_size_, width, lenght):
     y = (image.height - text_size[1]) / 2
     # Draw the text on the image
     draw.text((x, y), text, fill=(0, 0, 0), font=font)
+    print("end generation")
+
     return image
 
 def to_Canny(image):
-  # Let's load the popular vermeer image
-  image = np.array(image)
+    print("start canny")
 
-  low_threshold = 100
-  high_threshold = 200
+    # Let's load the popular vermeer image
+    image = np.array(image)
+    
+    low_threshold = 100
+    high_threshold = 200
+    
+    image = cv2.Canny(image, low_threshold, high_threshold)
+    image = image[:, :, None]
+    image = np.concatenate([image, image, image], axis=2)
+    canny_image = Image.fromarray(image)
+    print("end canny")
 
-  image = cv2.Canny(image, low_threshold, high_threshold)
-  image = image[:, :, None]
-  image = np.concatenate([image, image, image], axis=2)
-  canny_image = Image.fromarray(image)
-  return canny_image
+    return canny_image
 
 def inference(prompt,canny_image,number,seed ):
+    print("start inference")
+
     
     pipe.scheduler = UniPCMultistepScheduler.from_config(pipe.scheduler.config)
     # This command loads the individual model components on GPU on-demand. So, we don't
@@ -84,6 +93,7 @@ def inference(prompt,canny_image,number,seed ):
     prompt = prompt
     out_image = pipe(
       prompt, num_inference_steps=20, generator=generator, image=image_, num_images_per_prompt=number)
+    print('end inference')
     return out_image
     
 def generate_images(image, prompt):