Update app.py

app.py

@@ -1,30 +1,26 @@
-from transformers import TFAutoModel, AutoTokenizer
-
-tokenizer = AutoTokenizer.from_pretrained('ucaslcl/GOT-OCR2_0', trust_remote_code=True)
-model = TFAutoModel.from_pretrained('ucaslcl/GOT-OCR2_0', trust_remote_code=True, low_cpu_mem_usage=True, device_map='cuda', use_safetensors=True, pad_token_id=tokenizer.eos_token_id)
-model = model.eval().cuda()
-
-
-# input your test image
-image_file = 'input_data/ocr_input/shopping-1200-1667548245.jpg'
-
-# plain texts OCR
-res = model.chat(tokenizer, image_file, ocr_type='ocr')
-
-# format texts OCR:
-# res = model.chat(tokenizer, image_file, ocr_type='format')
-
-# fine-grained OCR:
-# res = model.chat(tokenizer, image_file, ocr_type='ocr', ocr_box='')
-# res = model.chat(tokenizer, image_file, ocr_type='format', ocr_box='')
-# res = model.chat(tokenizer, image_file, ocr_type='ocr', ocr_color='')
-# res = model.chat(tokenizer, image_file, ocr_type='format', ocr_color='')
-
-# multi-crop OCR:
-# res = model.chat_crop(tokenizer, image_file, ocr_type='ocr')
-# res = model.chat_crop(tokenizer, image_file, ocr_type='format')
-
-# render the formatted OCR results:
-# res = model.chat(tokenizer, image_file, ocr_type='format', render=True, save_render_file = './demo.html')
-
-print(res)
+import os
+os.system('pip install paddlepaddle')
+os.system('pip install paddleocr')
+import requests
+from paddleocr import PaddleOCR, draw_ocr
+from PIL import Image
+import gradio as gr
+
+img = "input_data/ocr_input/39890867421_3fa100d185_z.jpg"
+
+def inference(img, lang):
+	ocr = PaddleOCR(use_angle_cls=True, lang=lang,use_gpu=False)
+	img_path = img  
+	result = ocr.ocr(img_path, cls=True)[0]
+	image = Image.open(img_path).convert('RGB')
+	boxes = [line[0] for line in result]
+	txts = [line[1][0] for line in result]
+	scores = [line[1][1] for line in result]
+    return txts
+	# im_show = draw_ocr(image, boxes, txts, scores,
+	# 		   font_path='./simfang.ttf')
+	# im_show = Image.fromarray(im_show)
+	# im_show.save('result.jpg')
+	# return 'result.jpg'
+
+print(inference(img,"ko"))