Create app.py

app.py

@@ -0,0 +1,28 @@
+
+import gradio
+from diffusers import StableDiffusionPipeline
+import requests
+from PIL import Image
+from transformers import BlipProcessor, BlipForConditionalGeneration
+
+pipe = StableDiffusionPipeline.from_pretrained("ByteDance/sd2.1-base-zsnr-laionaes6")#.to("cuda")
+processor = BlipProcessor.from_pretrained("Salesforce/blip-image-captioning-large")
+model = BlipForConditionalGeneration.from_pretrained("Salesforce/blip-image-captioning-large")
+
+def img2prompt(img):
+    raw_image = img.convert("RGB")
+    inputs = processor(raw_image, return_tensors="pt")
+    out = model.generate(**inputs)
+    output = processor.decode(out[0], skip_special_tokens=True)
+    return output
+
+def prompt2img(prompt):
+    pipe = StableDiffusionPipeline.from_pretrained("ByteDance/sd2.1-base-zsnr-laionaes6").to("cuda")
+    img = pipe(prompt, guidance_scale=7.5, guidance_rescale=0.7).images[0]
+    return img
+
+def wow_img2img(img):
+    return prompt2img(img2prompt(img))
+
+app = gradio.Interface(fn=wow_img2img, inputs=gradio.Image(type="pil"), outputs=gradio.Image(type="pil"))
+app.launch(share=True)