Spaces:
Running
Running
File size: 1,381 Bytes
3f99757 d8e83d9 3f99757 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 |
#imagetext-to-text
import gradio as gr
import base64
from huggingface_hub import InferenceClient
client = InferenceClient('nanonets/Nanonets-OCR-s')
def imageDescription(image, prompt):
image_path="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")
with gr.Column():
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)
#sending two inputs to imageDescription function
describe_btn.click(fn=imageDescription, inputs=[image, prompt], outputs=output)
demo.launch(debug=True)
|