bugfix

app.py

@@ -42,15 +42,21 @@ 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:
             print(f"Elapsed time: {self.elapsed_time:.6f} seconds")
+        
+        print(f"Activity: {self.activity_name}, End time: {self.start_time_formatted}")
 
 # 生成图像的函数
 @spaces.GPU
@@ -60,6 +66,7 @@ def generate_image(prompt, steps, seed, cfg_scale, width, height, progress):
     generator = torch.Generator(device=device).manual_seed(seed)
     with calculateDuration("Generating image"):
         # Generate image
+        print(prompt, steps, seed, cfg_scale, width, height)
         generated_image = pipe(
             prompt=prompt,
             num_inference_steps=steps,
@@ -95,7 +102,7 @@ def upload_image_to_r2(image, account_id, access_key, secret_key, bucket_name):
     
     return image_file
 
-def run_lora(prompt, lora_strings_json,  cfg_scale, steps, randomize_seed, seed, width, height, lora_scale, upload_to_r2, account_id, access_key, secret_key, bucket, progress=gr.Progress(track_tqdm=True)):
+def run_lora(prompt, lora_strings_json,  cfg_scale, steps, randomize_seed, seed, width, height, upload_to_r2, account_id, access_key, secret_key, bucket, progress=gr.Progress(track_tqdm=True)):
     
     # Load LoRA weights
     if lora_strings_json:
@@ -164,14 +171,13 @@ with gr.Blocks(css=css) as demo:
                 with gr.Row():
                     seed = gr.Slider(label="Seed", minimum=0, maximum=MAX_SEED, step=1, value=0, randomize=True)
                     randomize_seed = gr.Checkbox(label="Randomize seed", value=True)
-                    lora_scale = gr.Slider(label="LoRA Scale", minimum=0, maximum=1, step=0.01, value=0.5)
 
                 with gr.Row():
-                    width = gr.Slider(label="Width", minimum=256, maximum=1536, step=64, value=512)
-                    height = gr.Slider(label="Height", minimum=256, maximum=1536, step=64, value=512)
+                    width = gr.Slider(label="Width", minimum=256, maximum=1536, step=64, value=1024)
+                    height = gr.Slider(label="Height", minimum=256, maximum=1536, step=64, value=1024)
 
                 with gr.Row():
-                    cfg_scale = gr.Slider(label="CFG Scale", minimum=1, maximum=20, step=0.5, value=7.5)
+                    cfg_scale = gr.Slider(label="CFG Scale", minimum=1, maximum=20, step=0.5, value=3.5)
                     steps = gr.Slider(label="Steps", minimum=1, maximum=50, step=1, value=28) 
 
                 upload_to_r2 = gr.Checkbox(label="Upload to R2", value=False)
@@ -195,7 +201,6 @@ with gr.Blocks(css=css) as demo:
         seed,
         width,
         height,
-        lora_scale,
         upload_to_r2,
         account_id,
         access_key,