Updated from colab

app.py

@@ -0,0 +1,38 @@
+
+import gradio as gr
+from diffusers import StableDiffusionPipeline
+
+pipe = StableDiffusionPipeline.from_pretrained("CompVis/stable-diffusion-v1-4")
+pipe = pipe.to("cuda")
+client = Client('abidlabs/GFPGAN')
+
+# setting=Tom Hanks nightwing in real life camera, high-def, high-res, 4k, dark night, raining, thunder
+def predict(celebrity, movie,setting):
+  prompt=f" Create a movie poster featuring {celebrity} along with the movie title. The poster should include the title of the movie as {movie},and in a given settings as {setting}"
+  image = pipe(prompt).images[0]
+  tmpFileName = 'tmp_image.png'
+  image.save(tmpFileName, 'PNG')
+  gfpGanFileName = client.predict(tmpFileName, 2)
+
+  return Image.open(gfpGanFileName)
+
+import gradio as gr
+import os
+
+HF_TOKEN = os.getenv('HF_TOKEN')
+hf_writer =  gr.HuggingFaceDatasetSaver(HF_TOKEN, "movie-poster")
+
+gr.Interface(
+  fn = predict,  
+    inputs=[
+        gr.inputs.Textbox(label="celebrity"),
+        gr.inputs.Dropdown(label="Movies", choices=["Batman", "Gladiator", "Mission Impossible"]),
+        gr.inputs.Textbox(label="Setting")               
+    ],
+    outputs= gr.outputs.Image(label="Generated movie poster",type='pil'),
+    description="Generate a movie poster with the given information",
+    title = "Movie Poster Generator",
+    allow_flagging="manual",
+    flagging_options=["Good", "Better", "Worst"],
+    flagging_callback=hf_writer
+).launch(share=True)

requirements.txt

@@ -0,0 +1,5 @@
+transformers
+huggingface_hub
+diffusers
+gradio
+Pillow