Spaces:
Running
on
T4
Running
on
T4
File size: 7,139 Bytes
b9dea2c ee94965 dbb32ab ee94965 dbb32ab 714f9cb b9dea2c dbb32ab 714f9cb dbb32ab b9dea2c 714f9cb 2c60ec4 714f9cb 2c60ec4 dbb32ab 714f9cb b44d45c 714f9cb b44d45c 714f9cb dbb32ab 82673a2 b44d45c 714f9cb dbb32ab b44d45c dbb32ab b44d45c 9aaed47 dbb32ab 714f9cb b44d45c 714f9cb dbb32ab b9dea2c dbb32ab 714f9cb b44d45c 714f9cb b44d45c 714f9cb dbb32ab b44d45c 714f9cb dbb32ab b44d45c dbb32ab 714f9cb b44d45c 714f9cb dbb32ab 714f9cb b9dea2c b44d45c ee94965 b3bb9ad b44d45c b3bb9ad b44d45c b3bb9ad b44d45c b3bb9ad b44d45c b3bb9ad b44d45c b3bb9ad b44d45c b3bb9ad b44d45c b9dea2c b44d45c |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 |
import gradio as gr
import json
import subprocess
from PIL import Image
import os
import tempfile
import logging
# Configuração básica de logging
logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')
def save_temp_image(img):
temp_dir = tempfile.mkdtemp()
img_path = os.path.join(temp_dir, "input_image.png")
img.save(img_path)
logging.info(f"Imagem salva em {img_path}")
return img_path, temp_dir
def run_command(command):
logging.info(f"Executing command: {command}") # Adiciona o log do comando
try:
result = subprocess.check_output(command, shell=True, stderr=subprocess.STDOUT, encoding='utf-8')
logging.info("Command Output: " + result)
return result
except subprocess.CalledProcessError as e:
logging.error(f"Command failed with error: {e.output}")
return None
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}"
if run_command(command) is None:
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"
# Limpeza movida para depois da leitura dos resultados
os.remove(img_path)
logging.info(f"Limpeza concluída para {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}"
if run_command(command) is None:
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"}
# Limpeza movida para depois da leitura dos resultados
os.remove(img_path)
logging.info(f"Limpeza concluída para {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() |