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from paddleocr import PaddleOCR
import requests
import numpy as np
from PIL import Image
from io import BytesIO
import json
import gradio as gr
import paddleocr
# ocr = PaddleOCR(use_angle_cls=True, lang='en', use_pdserving=False, cls_batch_num=8, det_batch_num=8, rec_batch_num=8)
ocr = PaddleOCR(use_angle_cls=True, lang='en')
def index(url):
response = requests.get(url)
img = Image.open(BytesIO(response.content))
resize_factor = 1
new_size = tuple(int(dim * resize_factor) for dim in img.size)
img = img.resize(new_size, Image.Resampling.LANCZOS)
img_array = np.array(img.convert('RGB'))
result = ocr.ocr(img_array)
boxes = [line[0] for line in result]
txts = [line[1][0] for line in result]
scores = [line[1][1] for line in result]
print(boxes)
print(txts)
output_dict = {"texts": txts, "boxes": boxes, "scores": scores}
output_json = json.dumps(output_dict) # Convert to JSON string
return output_json
inputs_image_url = [
gr.Textbox(type="text", label="Image URL"),
]
outputs_result_json = [
gr.Textbox(type="text", label="Result JSON"),
]
interface_image_url = gr.Interface(
fn=index,
inputs=inputs_image_url,
outputs=outputs_result_json,
title="Text Extraction",
cache_examples=False,
).queue().launch()
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