bugfix

app.py

@@ -54,11 +54,15 @@ class calculateDuration:
 
     def __enter__(self):
         self.start_time = time.time()
+        self.start_time_formatted = time.strftime("%Y-%m-%d %H:%M:%S", time.localtime(self.start_time))
+        print(f"Activity: {self.activity_name}, Start time: {self.start_time_formatted}")
         return self
     
     def __exit__(self, exc_type, exc_value, traceback):
         self.end_time = time.time()
         self.elapsed_time = self.end_time - self.start_time
+        self.end_time_formatted = time.strftime("%Y-%m-%d %H:%M:%S", time.localtime(self.end_time))
+        
         if self.activity_name:
             print(f"Elapsed time for {self.activity_name}: {self.elapsed_time:.6f} seconds")
         else:
@@ -113,7 +117,6 @@ def upload_image_to_r2(image, account_id, access_key, secret_key, bucket_name):
     with calculateDuration("Upload image"):
         print("upload_image_to_r2", account_id, access_key, secret_key, bucket_name)
         connectionUrl = f"https://{account_id}.r2.cloudflarestorage.com"
-
         s3 = boto3.client(
             's3',
             endpoint_url=connectionUrl,
@@ -121,7 +124,6 @@ def upload_image_to_r2(image, account_id, access_key, secret_key, bucket_name):
             aws_access_key_id=access_key,
             aws_secret_access_key=secret_key
         )
-
         current_time = datetime.now().strftime("%Y/%m/%d/%H%M%S")
         image_file = f"generated_images/{current_time}_{random.randint(0, MAX_SEED)}.png"
         buffer = BytesIO()
@@ -155,9 +157,7 @@ def run_flux(
         seed_slicer = random.randint(0, MAX_SEED)
     generator = torch.Generator().manual_seed(seed_slicer)
 
-    with calculateDuration("run pipe"):
-        print("start to run pipe", prompt)
-       
+    with calculateDuration("Run pipe"):       
         with torch.inference_mode():
             generated_image = pipe(
                 prompt=prompt,
@@ -236,7 +236,7 @@ def process(
     bucket:str,
     progress=gr.Progress(track_tqdm=True)
 ):
-    
+    print("process", image_url, mask_url, inpainting_prompt_text, lora_strings_json)
     result = {"status": "false", "message": ""}
     if not image_url:
         gr.Info("please enter image url for inpaiting")
@@ -249,28 +249,29 @@ def process(
         return  None, json.dumps(result)
     
 
-    with calculateDuration("load image"):
+    with calculateDuration("Load image"):
         image = load_image(image_url)
         mask = load_image(mask_url)
     
-    if not image or not mask:
-        gr.Info("Please upload an image & mask by url.")
-        result["message"] = "can not load image"
-        return None, json.dumps(result)
+        if not image or not mask:
+            gr.Info("Please upload an image & mask by url.")
+            result["message"] = "can not load image"
+            return None, json.dumps(result)
 
     # generate
-    with calculateDuration("resize & process mask"):
+    with calculateDuration("Resize & process mask"):
         width, height = calculate_image_dimensions_for_flux(original_resolution_wh=image.size)
         image = image.resize((width, height), Image.LANCZOS)
         mask = mask.resize((width, height), Image.LANCZOS)
         mask = process_mask(mask, mask_inflation=mask_inflation_slider, mask_blur=mask_blur_slider)
 
     control_image = generate_control_image(image, mask, width, height)
-    clear_cuda_cache()
+    # clear_cuda_cache()
 
     load_loras(lora_strings_json=lora_strings_json)
     
     try:
+        print("Start applying for zeroGPU resources ...")
         generated_image = run_flux(
             image=image,
             mask=mask,
@@ -299,8 +300,7 @@ def process(
             result = {"status": "success", "message": "upload image success", "url": url}    
         else:
             result = {"status": "success", "message": "Image generated but not uploaded"}
-    
-    clear_cuda_cache()
+            
     final_images = []
     final_images.append(image)
     final_images.append(mask)