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| import gradio as gr | |
| import requests | |
| import pandas as pd | |
| from PIL import Image | |
| import numpy as np | |
| import base64 | |
| API_URL = "https://api-inference.huggingface.co/models/AliGhiasvand86/gisha_digit_recognition" | |
| headers = {"Authorization": "Bearer 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"} | |
| def query(image_path): | |
| with open(image_path, "rb") as file: | |
| response = requests.post(API_URL, headers=headers, data=file.read()) | |
| return response.json() | |
| def save_array_as_image(array, image_path): | |
| # Convert the array to an image | |
| image = Image.fromarray(array) | |
| # Save the image to the specified path | |
| image.save(image_path) | |
| def classify_digit(image): | |
| # Save the image as a .png file | |
| image_path = "sketchpad.png" | |
| save_array_as_image(image, image_path) | |
| result = query(image_path) | |
| df = pd.DataFrame.from_records(result) | |
| return df | |
| iface = gr.Interface(fn=classify_digit, inputs='sketchpad', outputs=gr.outputs.Dataframe(), | |
| allow_flagging='never', description='Draw a Digit Below... (Draw in the centre for best results)', | |
| layout="horizontal") | |
| iface.launch(share=True, width=1000, height=1000) | |