Prioritize fidelity model in pipeline selection and update user prompts for clarity

app.py

@@ -293,13 +293,13 @@ dit4sr_device = 'cuda:0'
 
 llava_agent = LLavaAgent("liuhaotian/llava-v1.5-13b", LLaVA_device, load_8bit=True, load_4bit=False)
 
-# Get the validation pipeline
-pipeline_dit4sr_q = load_dit4sr_q_pipeline(args, dit4sr_device)
+# Get the validation pipeline - prioritize dit4sr_f
+pipeline_dit4sr_f = load_dit4sr_f_pipeline(args, dit4sr_device)
 
-# Only load dit4sr_f if load_both_models is True
-pipeline_dit4sr_f = None
+# Only load dit4sr_q if load_both_models is True
+pipeline_dit4sr_q = None
 if args.load_both_models == 'True':
-    pipeline_dit4sr_f = load_dit4sr_f_pipeline(args, dit4sr_device)
+    pipeline_dit4sr_q = load_dit4sr_q_pipeline(args, dit4sr_device)
 
 @spaces.GPU
 @torch.no_grad()
@@ -349,11 +349,11 @@ def process_sr(
 
     images = []
     
-    # Choose pipeline based on model selection
-    if model_choice == "dit4sr_f" and pipeline_dit4sr_f is not None:
-        pipeline = pipeline_dit4sr_f
-    else:
+    # Choose pipeline based on model selection - prioritize dit4sr_f
+    if model_choice == "dit4sr_q" and pipeline_dit4sr_q is not None:
         pipeline = pipeline_dit4sr_q
+    else:
+        pipeline = pipeline_dit4sr_f
     
     try:
         image = pipeline(
@@ -387,7 +387,7 @@ Intro= \
 if args.load_both_models == 'True':
     Prompt = \
     """
-    First, select your preferred model (dit4sr_q or dit4sr_f). \\
+    First, select your preferred model (fidelity first or quality first). \\
     Then, click \"Run LLAVA\" to generate an initial prompt based on the input image. \\
     Modify the prompt for higher accuracy if needed. \\
     Finally, click \"Run DiT4SR\" to generate the SR result." \
@@ -397,7 +397,7 @@ else:
     """
     Click \"Run LLAVA\" to generate an initial prompt based on the input image. \\
     Modify the prompt for higher accuracy if needed. \\
-    Finally, click \"Run DiT4SR\" to generate the SR result using dit4sr_q model." \
+    Finally, click \"Run DiT4SR\" to generate the SR result using fidelity first model." \
     """
 
 exaple_images = sorted(glob.glob('examples/*.png'))
@@ -414,16 +414,16 @@ with block:
             if args.load_both_models == 'True':
                 model_choice = gr.Dropdown(
                     label="Model Selection",
-                    choices=["dit4sr_q", "dit4sr_f"],
-                    value="dit4sr_q",
-                    info="Choose between dit4sr_q (default) and dit4sr_f models"
+                    choices=[("Quality First", "dit4sr_q"), ("Fidelity First", "dit4sr_f")],
+                    value="dit4sr_f",
+                    info="Choose between Quality First and Fidelity First models"
                 )
             else:
                 # Hidden component with default value when only one model is available
                 model_choice = gr.Dropdown(
                     label="Model Selection",
-                    choices=["dit4sr_q"],
-                    value="dit4sr_q",
+                    choices=["dit4sr_f"],
+                    value="dit4sr_f",
                     visible=False
                 )