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import gradio as gr
import base64
from huggingface_hub import InferenceClient
client = InferenceClient('meta-llama/Llama-3.2-11B-Vision-Instruct')
def imageDescription(image, prompt):
image_path="/images/image.png"
image.save(image_path)
with open(image_path, "rb") as f:
base64_image = base64.b64encode(f.read()).decode("utf-8")
image_url = f"data:image/png;base64,{base64_image}"
output = client.chat.completions.create(messages=[
{
"role": "user",
"content": [
{
"type": "image_url",
"image_url": {"url": image_url},
},
{
"type": "text",
"text": prompt,
},
],
},
],
)
return output.choices[0].message.content
with gr.Blocks(theme=gr.themes.Citrus()) as demo:
with gr.Row():
with gr.Column():
#an image input
image=gr.Image(type="pil", label="upload an immage")
prompt = gr.Textbox(label="What would you like to know about this picture?",scale=1)
describe_btn = gr.Button("Describe the image",scale=1)
output = gr.Textbox(label="Description",scale=1)
with gr.Column():
#sending two inputs to imageDescription function
describe_btn.click(fn=imageDescription, inputs=[image, prompt], outputs=output)
demo.launch(debug=True) |