#Importing the library
import keras_ocr
import gradio as gr


# keras-ocr will automatically download pretrained
# weights for the detector and recognizer.
pipeline = keras_ocr.pipeline.Pipeline()
def classify_image(file_name):
    images = [keras_ocr.tools.read(file_name.name.replace("\\",'/'))]
    prediction_groups = pipeline.recognize(images)
    text = ""
    for i in prediction_groups[0]:
      text =  text+ " " + i[0]
    return text


image = gr.inputs.File( file_count="single",type="file", label="Fichier image à Traiter ")
# label = gr.outputs.Label(num_top_classes=3)

gr.Interface(
    fn=classify_image, 
    inputs=image, 
    outputs="text", 
    interpretation="default",
    title="API OCR",
    description="Cette API est utilisé extraire du texte dans une image"
).launch()