troubleshooting

app.py

@@ -95,34 +95,43 @@ async def run_virtual_tryon_pipeline(
         r.set(request_id, "checking incoming data...")
         front_type = ""
         back_type = ""
-        if top_garment_image is None and bottom_garment_image is None:
+        
+        # Read all files once at the start
+        top_garment_data = await top_garment_image.read() if top_garment_image else None
+        bottom_garment_data = await bottom_garment_image.read() if bottom_garment_image else None
+        top_back_garment_data = await top_back_garment_image.read() if top_back_garment_image else None
+        bottom_back_garment_data = await bottom_back_garment_image.read() if bottom_back_garment_image else None
+
+        if top_garment_data is None and bottom_garment_data is None:
             return {"error": "Missing garment images"}
-        if top_garment_image or bottom_garment_image is None:
-            #this is a single image try on
+            
+        if top_garment_data and bottom_garment_data:
+            front_type = "double"
+        elif top_garment_data or bottom_garment_data:
             front_type = "single"
         else:
-            front_type = "double"
-        if top_back_garment_image is None and bottom_back_garment_image is None:
-            back_type = "none"
+            front_type = "none"
+
+        if top_back_garment_data and bottom_back_garment_data:
+            back_type = "double"
+        elif top_back_garment_data or bottom_back_garment_data:
+            back_type = "single"
         else:
-            if top_back_garment_image or bottom_back_garment_image is None:
-                #this is a single image try on for the back
-                back_type = "single"
-            else: 
-                back_type = "double"
+            back_type = "none"
+
         print(f"front_type: {front_type}")
         print(f"back_type: {back_type}")
         front_final_image = ""
         back_final_image = ""
 
         if front_type == "double":
-            front_final_image = await combine_images_side_by_side(await top_garment_image.read(), await bottom_garment_image.read()) 
+            front_final_image = await combine_images_side_by_side(top_garment_data, bottom_garment_data)
         if back_type == "double":
-            back_final_image = await combine_images_side_by_side(await top_back_garment_image.read(), await bottom_back_garment_image.read()) 
+            back_final_image = await combine_images_side_by_side(top_back_garment_data, bottom_back_garment_data)
         if front_type == "single":
-            front_final_image = await top_garment_image.read()
+            front_final_image = top_garment_data or bottom_garment_data
         if back_type == "single":
-            back_final_image = await top_back_garment_image.read()
+            back_final_image = top_back_garment_data or bottom_back_garment_data
         r.set(request_id, "Garment images combined")   
         #Check incoming data. do we have the required data. Are the images what we expect? (ie flatlay image file etc.)
         #lets use openai for this. Also, return errors where needed

base_generator.py

@@ -52,7 +52,7 @@ def on_queue_update(update):
 def create_image(character_lora, character_keyword, outfit_desc, pose_id, num_outputs): 
     seed = random.randint(0, 1000000)
     print(f"seed: {seed}")
-    prompt = "Fashion model {character_keyword} wearing {outfit_desc}. posing in front of white background"
+    prompt = f"Fashion model {character_keyword} wearing {outfit_desc}. posing in front of white background"
 
     result = fal_client.subscribe(
         "fal-ai/flux-general",