Create app.py

app.py

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+import gradio as gr
+import torch
+from PIL import Image
+from diffusers import AutoPipelineForText2Image, DDIMScheduler
+from transformers import CLIPVisionModelWithProjection
+import numpy as np
+import spaces  # Ensure this is available in your environment
+
+# Initialize a zero tensor for demonstration purposes
+zero = torch.Tensor([0]).cuda()
+print(zero.device)  # Should output 'cuda:0' if a GPU is available
+
+@spaces.GPU  # Decorate the function to run on GPU
+def transform_image(face_image):
+    print(zero.device)  # Check the device inside the function, should be 'cuda:0'
+    
+    generator = torch.Generator(device="cuda").manual_seed(0)  # Use GPU device if available
+
+    # Process the input face image
+    if isinstance(face_image, Image.Image):
+        processed_face_image = face_image
+    elif isinstance(face_image, np.ndarray):
+        processed_face_image = Image.fromarray(face_image)
+    else:
+        raise ValueError("Unsupported image format")
+
+    # Load the style image from the local path
+    style_image_path = "/content/soyjak2.jpeg"
+    style_image = Image.open(style_image_path)
+
+    # Perform the transformation using the GPU
+    image = pipeline(
+        prompt="soyjak",
+        ip_adapter_image=[style_image, processed_face_image],
+        negative_prompt="monochrome, lowres, bad anatomy, worst quality, low quality",
+        num_inference_steps=30,
+        generator=generator,
+    ).images[0]
+
+    return image
+
+# Load models and configure pipeline with GPU support
+pipeline = AutoPipelineForText2Image.from_pretrained(
+    "stabilityai/stable-diffusion-xl-base-1.0",
+    torch_dtype=torch.float16,  # Consider using torch.float32 for GPU computations
+    device="cuda",  # Use GPU device if available
+).to("cuda")  # Ensure the model is moved to GPU
+
+# Additional pipeline configurations
+pipeline.scheduler = DDIMScheduler.from_config(pipeline.scheduler.config).to("cuda")
+pipeline.enable_model_cpu_offload(False)  # Consider not offloading to CPU when using GPU
+
+# Gradio interface setup
+demo = gr.Interface(
+    fn=transform_image,
+    inputs=gr.Image(label="Upload your face image"),
+    outputs=gr.Image(label="Your Soyjak"),
+    title="InstaSoyjak - turn anyone into a Soyjak",
+    description="All you need to do is upload an image. Please use responsibly. Please follow me on Twitter if you like this space: https://twitter.com/angrypenguinPNG. Idea from Yacine, please give him a follow: https://twitter.com/yacineMTB.",
+)
+
+demo.launch()