Create app.py

app.py

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+import gradio as gr
+from diffusers import DiffusionPipeline
+from transformers import pipeline
+
+get_caption = pipeline("image-to-text",model="Salesforce/blip-image-captioning-base")
+
+def captioner(input):
+    output = get_caption(input)
+    return output[0]['generated_text']
+
+generate_pipeline = DiffusionPipeline.from_pretrained("runwayml/stable-diffusion-v1-5")
+
+def generate(prompt):
+    return generate_pipeline(prompt).images[0]
+
+def caption_and_generate(image):
+    caption = captioner(image)
+    image = generate(caption)
+    return [caption, image]
+
+with gr.Blocks() as demo:
+    gr.Markdown("# Describe-and-Generate game 🖍️")
+    image_upload = gr.Image(label="Your first image",type="pil")
+    btn_all = gr.Button("Caption and generate")
+    caption = gr.Textbox(label="Generated caption")
+    image_output = gr.Image(label="Generated Image")
+
+    btn_all.click(fn=caption_and_generate, inputs=[image_upload], outputs=[caption, image_output])
+
+demo.launch()