Update app.py

app.py

@@ -5,13 +5,12 @@ import numpy as np
 import cv2
 from PIL import Image
 import spaces
-import io
+
 
 # 🌟 Auto-detect device (CPU/GPU)
 device = "cuda"
 precision = torch.float16
 
-
 # 🏗️ Load ControlNet model for Canny edge detection
 # xinsir/controlnet-canny-sdxl-1.0
 # diffusers/controlnet-canny-sdxl-1.0
@@ -26,6 +25,7 @@ vae = AutoencoderKL.from_pretrained("madebyollin/sdxl-vae-fp16-fix", torch_dtype
 # Scheduler
 eulera_scheduler = EulerAncestralDiscreteScheduler.from_pretrained("stabilityai/stable-diffusion-xl-base-1.0", subfolder="scheduler")
 
+# Stable Diffusion Model
 pipe = StableDiffusionXLControlNetPipeline.from_pretrained(
     "stabilityai/stable-diffusion-xl-base-1.0",
     controlnet=controlnet,
@@ -58,12 +58,8 @@ def generate_image(prompt, input_image, low_threshold, high_threshold, strength,
         controlnet_conditioning_scale=float(controlnet_conditioning_scale),
         strength=strength
     ).images[0]
-
-    result_buffer = io.BytesIO()
-    result.save(result_buffer, format="JPEG")
-    result_buffer.seek(0)
     
-    return edge_detected, result_buffer
+    return edge_detected, result
 
 # 🖥️ Gradio UI
 with gr.Blocks() as demo: