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| import cv2 | |
| import easyocr | |
| import gradio as gr | |
| from main import predict_mcq | |
| reader = easyocr.Reader(['th','en']) | |
| def ocr_with_easy(image): | |
| #gray_scale_image=get_grayscale(img) | |
| #thresholding(gray_scale_image) | |
| cv2.imwrite('image.png',image) | |
| bounds = reader.readtext(image,paragraph="False",detail = 0) | |
| bounds = ''.join(bounds) | |
| return bounds | |
| def put_in_single_list(data): | |
| result=[] | |
| final_result=[] | |
| for i in data: | |
| result.append(i.get("question_statement")) | |
| result.append(i.get("answer")) | |
| result.append(i.get("options")) | |
| final_result.append(result) | |
| return final_result | |
| def MCQGenerator(image): | |
| I_text=ocr_with_easy(image) | |
| text={ | |
| "input_text":I_text | |
| } | |
| Mcqs=predict_mcq(text) | |
| data=Mcqs.get('questions') | |
| final_result=put_in_single_list(data) | |
| return final_result | |
| iface=gr.Interface(fn=MCQGenerator,inputs="image",outputs=[gr.components.Textbox(label="MCQS")], | |
| examples=[['demo.PNG']]) | |
| iface.launch(debug=True) |