Update main.py

main.py

@@ -1,11 +1,3 @@
-import tensorflow as tf
-
-# Detect and init the GPU
-physical_devices = tf.config.list_physical_devices('GPU')
-if len(physical_devices) > 0:
-    tf.config.set_visible_devices(physical_devices[0], 'GPU')
-    tf.config.experimental.set_memory_growth(physical_devices[0], True)
-
 import io
 import os
 from flask import Flask, request, jsonify
@@ -18,15 +10,19 @@ from keras.applications.xception import Xception # to get pre-trained model Xcep
 from keras.models import load_model
 from keras.preprocessing.sequence import pad_sequences
 
+print(os.popen(f'cat /etc/debian_version').read())
+print(os.popen(f'cat /etc/issue').read())
+print(os.popen(f'apt search tesseract').read())
+
 app = Flask(__name__)
 
 MAX_LENGTH = 38
 
 # Set the TESSDATA_PREFIX environment variable
-os.environ['TESSDATA_PREFIX'] = '/usr/share/tesseract-ocr/4.00/tessdata'
+# os.environ['TESSDATA_PREFIX'] = '/cache/huggingface/downloads/tesseract-ocr/4.00/tessdata'
 
 # Set the path to the Tesseract executable
-pytesseract.pytesseract.tesseract_cmd = r'/usr/bin/tesseract'
+# pytesseract.pytesseract.tesseract_cmd = r'/usr/bin/tesseract'
 
 def format_tesseract_output(output_text):
     formatted_text = ""
@@ -92,7 +88,7 @@ def generate_caption():
         # Convert the image data to a PIL image object
         pil_image = Image.open(io.BytesIO(image_data))
         
-        extracted_text = pytesseract.image_to_string(pil_image, lang="eng+chi_sim+msa")
+        extracted_text = pytesseract.image_to_string(pil_image)
         hasText = bool(extracted_text.strip())
         
         if hasText: