Create app.py

app.py

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+#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 à Traiter (sous fichier .pgm)")
+# label = gr.outputs.Label(num_top_classes=3)
+
+gr.Interface(
+    fn=classify_image, 
+    inputs=image, 
+    outputs="text", 
+    interpretation="default",
+    live=True,
+    theme="dark-peach",
+    title="API OCR",
+    description="Cette API est utilisé extraire du texte dans une image"
+).launch()