Surya-OCR / app.py
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import gradio as gr
import json
import subprocess
from PIL import Image
import os
import tempfile
def save_temp_image(img):
temp_dir = tempfile.mkdtemp()
img_path = os.path.join(temp_dir, "input_image.png")
img.save(img_path)
return img_path, temp_dir
def ocr_function_cli(img, lang_name):
img_path, temp_dir = save_temp_image(img)
command = f"surya_ocr {img_path} --langs {lang_name} --images --results_dir {temp_dir}"
try:
subprocess.run(command, shell=True, check=True, encoding='utf-8')
except subprocess.CalledProcessError as e:
print(f"OCR command failed: {e.output}")
return img, "OCR failed"
result_img_path = os.path.join(temp_dir, "image_with_text.png")
result_text_path = os.path.join(temp_dir, "results.json")
if os.path.exists(result_img_path):
result_img = Image.open(result_img_path)
else:
result_img = img
if os.path.exists(result_text_path):
with open(result_text_path, "r", encoding='utf-8') as file:
result_text = json.load(file)
text_output = "\n".join([str(page) for page in result_text.values()])
else:
text_output = "No text detected"
os.remove(img_path)
return result_img, text_output
def text_line_detection_function_cli(img):
img_path, temp_dir = save_temp_image(img)
command = f"surya_detect {img_path} --images --results_dir {temp_dir}"
try:
subprocess.run(command, shell=True, check=True, encoding='utf-8')
except subprocess.CalledProcessError as e:
print(f"Text line detection command failed: {e.output}")
return img, {"error": "Detection failed"}
result_img_path = os.path.join(temp_dir, "image_with_lines.png")
result_json_path = os.path.join(temp_dir, "results.json")
if os.path.exists(result_img_path):
result_img = Image.open(result_img_path)
else:
result_img = img
if os.path.exists(result_json_path):
with open(result_json_path, "r", encoding='utf-8') as file:
result_json = json.load(file)
else:
result_json = {"error": "No detection results found"}
os.remove(img_path)
return result_img, result_json
with gr.Blocks() as app:
gr.Markdown("# Surya OCR and Text Line Detection via CLI")
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=[
"Afrikaans",
"Amharic",
"Arabic",
"Assamese",
"Azerbaijani",
"Belarusian",
"Bulgarian",
"Bengali",
"Breton",
"Bosnian",
"Catalan",
"Czech",
"Welsh",
"Danish",
"German",
"Greek",
"English",
"Esperanto",
"Spanish",
"Estonian",
"Basque",
"Persian",
"Finnish",
"French",
"Western Frisian",
"Irish",
"Scottish Gaelic",
"Galician",
"Gujarati",
"Hausa",
"Hebrew",
"Hindi",
"Croatian",
"Hungarian",
"Armenian",
"Indonesian",
"Icelandic",
"Italian",
"Japanese",
"Javanese",
"Georgian",
"Kazakh",
"Khmer",
"Kannada",
"Korean",
"Kurdish",
"Kyrgyz",
"Latin",
"Lao",
"Lithuanian",
"Latvian",
"Malagasy",
"Macedonian",
"Malayalam",
"Mongolian",
"Marathi",
"Malay",
"Burmese",
"Nepali",
"Dutch",
"Norwegian",
"Oromo",
"Oriya",
"Punjabi",
"Polish",
"Pashto",
"Portuguese",
"Romanian",
"Russian",
"Sanskrit",
"Sindhi",
"Sinhala",
"Slovak",
"Slovenian",
"Somali",
"Albanian",
"Serbian",
"Sundanese",
"Swedish",
"Swahili",
"Tamil",
"Telugu",
"Thai",
"Tagalog",
"Turkish",
"Uyghur",
"Ukrainian",
"Urdu",
"Uzbek",
"Vietnamese",
"Xhosa",
"Yiddish",
"Chinese"
],
value="English"
)
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_cli, inputs=[ocr_input_image, ocr_language_selector], outputs=[ocr_output_image, ocr_text_output]
)
with gr.Tab("Text Line Detection"):
with gr.Column():
detection_input_image = gr.Image(label="Input Image for Detection", type="pil")
detection_run_button = gr.Button("Run Text Line Detection")
with gr.Column():
detection_output_image = gr.Image(label="Detection Output Image", type="pil", interactive=False)
detection_json_output = gr.JSON(label="Detection JSON Output")
detection_run_button.click(
fn=text_line_detection_function_cli, inputs=detection_input_image, outputs=[detection_output_image, detection_json_output]
)
if __name__ == "__main__":
app.launch()