import os import shutil import uuid import fitz # PyMuPDF import gradio as gr from modelscope import AutoModel, AutoTokenizer from PIL import Image, ImageEnhance from got_ocr import got_ocr # 初始化模型和分词器 tokenizer = AutoTokenizer.from_pretrained("stepfun-ai/GOT-OCR2_0", trust_remote_code=True) model = AutoModel.from_pretrained("stepfun-ai/GOT-OCR2_0", trust_remote_code=True, low_cpu_mem_usage=True, device_map="cuda", use_safetensors=True) model = model.eval().cuda() UPLOAD_FOLDER = "./uploads" RESULTS_FOLDER = "./results" # 确保必要的文件夹存在 os.makedirs(UPLOAD_FOLDER, exist_ok=True) os.makedirs(RESULTS_FOLDER, exist_ok=True) def pdf_to_images(pdf_path): images = [] pdf_document = fitz.open(pdf_path) for page_num in range(len(pdf_document)): page = pdf_document.load_page(page_num) # 进一步增加分辨率和缩放比例 zoom = 4 # 增加缩放比例到4 mat = fitz.Matrix(zoom, zoom) pix = page.get_pixmap(matrix=mat, alpha=False) img = Image.frombytes("RGB", [pix.width, pix.height], pix.samples) # 增加对比度 enhancer = ImageEnhance.Contrast(img) img = enhancer.enhance(1.5) # 增加50%的对比度 images.append(img) pdf_document.close() return images def process_pdf(pdf_file): if pdf_file is None: return None temp_pdf_path = os.path.join(UPLOAD_FOLDER, f"{uuid.uuid4()}.pdf") # 使用 shutil 复制上传的件到临时位置 shutil.copy(pdf_file.name, temp_pdf_path) images = pdf_to_images(temp_pdf_path) os.remove(temp_pdf_path) # 将图像保存为临时文件并返回文件路径列表 image_paths = [] for i, img in enumerate(images): img_path = os.path.join(RESULTS_FOLDER, f"page_{i+1}.png") img.save(img_path, "PNG") image_paths.append(img_path) return image_paths def on_image_select(evt: gr.SelectData): if evt.index is not None: return evt.index return None # 更新perform_ocr函数的输入参数 def perform_ocr(selected_index, image_gallery, task, fine_grained_type, color, box): if selected_index is None or len(image_gallery) == 0: return "请先选择一张图片" selected_image = image_gallery[selected_index] # 根据选择的任务和参数调用GOT OCR got_mode = task ocr_color = color if fine_grained_type == "color" else "" ocr_box = box if fine_grained_type == "box" else "" result, _ = got_ocr(model, tokenizer, selected_image, got_mode=got_mode, fine_grained_mode=fine_grained_type, ocr_color=ocr_color, ocr_box=ocr_box) return result with gr.Blocks() as demo: pdf_input = gr.File(label="上传PDF文件") image_gallery = gr.Gallery(label="PDF页面预览", columns=3, height="auto") selected_index = gr.State(None) task_dropdown = gr.Dropdown( choices=[ "plain texts OCR", "format texts OCR", "plain multi-crop OCR", "format multi-crop OCR", "plain fine-grained OCR", "format fine-grained OCR", ], label="选择GOT模式", value="plain texts OCR", ) fine_grained_dropdown = gr.Dropdown(choices=["box", "color"], label="fine-grained类型", visible=False) color_dropdown = gr.Dropdown(choices=["red", "green", "blue"], label="颜色列表", visible=False) box_input = gr.Textbox(label="输入框: [x1,y1,x2,y2]", placeholder="例如: [0,0,100,100]", visible=False) def task_update(task): if "fine-grained" in task: return [ gr.update(visible=True), gr.update(visible=False), gr.update(visible=False), ] else: return [ gr.update(visible=False), gr.update(visible=False), gr.update(visible=False), ] def fine_grained_update(fine_grained_type): if fine_grained_type == "color": return [ gr.update(visible=True), gr.update(visible=False), ] elif fine_grained_type == "box": return [ gr.update(visible=False), gr.update(visible=True), ] else: return [ gr.update(visible=False), gr.update(visible=False), ] task_dropdown.change(task_update, inputs=[task_dropdown], outputs=[fine_grained_dropdown, color_dropdown, box_input]) fine_grained_dropdown.change(fine_grained_update, inputs=[fine_grained_dropdown], outputs=[color_dropdown, box_input]) ocr_button = gr.Button("开始OCR识别") ocr_result = gr.Textbox(label="OCR结果") # 更新ocr_button的click事件,传递所有必要的参数 ocr_button.click( fn=perform_ocr, inputs=[selected_index, image_gallery, task_dropdown, fine_grained_dropdown, color_dropdown, box_input], outputs=ocr_result ) pdf_input.upload(fn=process_pdf, inputs=pdf_input, outputs=image_gallery) image_gallery.select(fn=on_image_select, inputs=[], outputs=selected_index) ocr_button.click(fn=perform_ocr, inputs=[selected_index, image_gallery], outputs=ocr_result) # 移除了选中图片的显示部分 if __name__ == "__main__": demo.launch()