Update app.py

app.py

@@ -6,6 +6,7 @@ import torch
 import base64
 from io import BytesIO
 from PIL import Image
+import tempfile
 
 device = "cuda" if torch.cuda.is_available() else "cpu"
 
@@ -22,7 +23,7 @@ MAX_SEED = np.iinfo(np.int32).max
 MAX_IMAGE_SIZE = 1024
 
 def infer(prompt_part1, color, dress_type, design, prompt_part5, negative_prompt, seed, randomize_seed, width, height, guidance_scale, num_inference_steps):
-    prompt = f"{prompt_part1} {color} colored {dress_type} with {design} design, {prompt_part5}"
+    prompt = f"{prompt_part1} {color} colored {dress_type} with {design} design, {prompt_part5} and also show the back, left and right side of the cloth in the form of collage with the front view"
     
     if randomize_seed:
         seed = random.randint(0, MAX_SEED)
@@ -39,12 +40,12 @@ def infer(prompt_part1, color, dress_type, design, prompt_part5, negative_prompt
         generator=generator
     ).images[0] 
 
-    # Convert the PIL image to base64
-    buffered = BytesIO()
-    image.save(buffered, format="PNG")
-    img_str = base64.b64encode(buffered.getvalue()).decode("utf-8")
+    # Save the image to a temporary file
+    with tempfile.NamedTemporaryFile(delete=False, suffix=".png") as temp_file:
+        image.save(temp_file, format="PNG")
+        temp_file_path = temp_file.name
     
-    return img_str
+    return temp_file_path
 
 examples = [
     ["red", "t-shirt", "yellow stripes"],