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Running
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T4
import gradio as gr | |
import json | |
from PIL import Image | |
from surya.ocr import run_ocr | |
from surya.detection import batch_detection | |
from surya.model.detection.segformer import load_model as load_det_model, load_processor as load_det_processor | |
from surya.model.recognition.model import load_model as load_rec_model | |
from surya.model.recognition.processor import load_processor as load_rec_processor | |
from surya.postprocessing.heatmap import draw_polys_on_image | |
# Load models and processors | |
det_model, det_processor = load_det_model(), load_det_processor() | |
rec_model, rec_processor = load_rec_model(), load_rec_processor() | |
# Assuming languages.json maps language codes to names, but we'll use codes directly for dropdown | |
with open("languages.json", "r") as file: | |
languages = json.load(file) | |
language_options = list(languages.keys()) # Use codes directly | |
def ocr_function(img, lang_code): | |
predictions = run_ocr([img], [lang_code], det_model, det_processor, rec_model, rec_processor) | |
# Assuming predictions is a list of dictionaries, one per image | |
if predictions: | |
img_with_text = draw_polys_on_image(predictions[0]["polys"], img) | |
return img_with_text, predictions[0] | |
else: | |
return img, {"error": "No text detected"} | |
def text_line_detection_function(img): | |
preds = batch_inference([img], det_model, det_processor)[0] | |
img_with_lines = draw_polys_on_image(preds["polygons"], img) | |
return img_with_lines, preds | |
with gr.Blocks() as app: | |
gr.Markdown("# Surya OCR e Detecção de Linhas de Texto") | |
with gr.Tab("OCR"): | |
with gr.Column(): | |
ocr_input_image = gr.Image(label="Input Image for OCR", type="pil") | |
ocr_language_selector = gr.Dropdown(label="Select Language for OCR", choices=language_options, value="en") | |
ocr_run_button = gr.Button("Run OCR") | |
with gr.Column(): | |
ocr_output_image = gr.Image(label="OCR Output Image", type="pil", interactive=False) | |
ocr_text_output = gr.TextArea(label="Recognized Text") | |
ocr_run_button.click(fn=ocr_function, inputs=[ocr_input_image, ocr_language_selector], outputs=[ocr_output_image, ocr_text_output]) | |
with gr.Tab("Detecção de Linhas de Texto"): | |
with gr.Column(): | |
detection_input_image = gr.Image(label="Imagem de Entrada para Detecção", type="pil") | |
detection_run_button = gr.Button("Executar Detecção de Linhas de Texto") | |
with gr.Column(): | |
detection_output_image = gr.Image(label="Imagem de Saída da Detecção", type="pil", interactive=False) | |
detection_json_output = gr.JSON(label="Saída JSON da Detecção") | |
detection_run_button.click(fn=text_line_detection_function, inputs=detection_input_image, outputs=[detection_output_image, detection_json_output]) | |
if __name__ == "__main__": | |
app.launch() | |