Update app.py

app.py

@@ -1,26 +1,27 @@
-import streamlit as st
-from transformers import pipeline
-from PIL import Image
-import requests
-pip install transformers torch
+pip install invisible_watermark transformers accelerate safetensors
 
 
-classifier = pipeline("image-classification", model="google/vit-base-patch16-224")
+from diffusers import StableDiffusionXLPipeline, EulerAncestralDiscreteScheduler
 
-def get_img_from_url(url):
-    return Image.open(requests.get(url, stream=True).raw)
+pipe = StableDiffusionXLPipeline.from_pretrained(
+    "hotshotco/SDXL-512",
+    use_safetensors=True,
+).to('cuda')
 
-def main():
-    st.title("Image Classification")
+pipe.scheduler = EulerAncestralDiscreteScheduler.from_config(pipe.scheduler.config)
 
-    with st.form("image"):
-        url = st.text_input("URL ของรูปภาพ", "https://images.livemint.com/img/2022/08/01/600x338/Cat-andriyko-podilnyk-RCfi7vgJjUY-unsplash_1659328989095_1659328998370_1659328998370.jpg")
-        img = get_img_from_url(url)
-        clicked = st.form_submit_button("ส่งคำขอ")
-        
-        if clicked:
-            results = classifier(img)
-            st.json(results)
+prompt = "a woman laughing"
+negative_prompt = ""
+
+image = pipe(
+    prompt,
+    negative_prompt=negative_prompt,
+    width=512,
+    height=512,
+    target_size=(1024, 1024),
+    original_size=(4096, 4096),
+    num_inference_steps=50
+).images[0]
+
+image.save("woman_laughing.png")
 
-if __name__ == "__main__":
-    main()