prithivMLmods
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Upload ocrtest_qwen.ipynb
Browse files- Demo/ocrtest_qwen.ipynb +556 -0
Demo/ocrtest_qwen.ipynb
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{
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"nbformat": 4,
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"nbformat_minor": 0,
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"metadata": {
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"colab": {
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"provenance": [],
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"gpuType": "T4"
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},
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"kernelspec": {
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"name": "python3",
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"display_name": "Python 3"
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},
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"language_info": {
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"name": "python"
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},
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"accelerator": "GPU"
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},
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"cells": [
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{
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"cell_type": "markdown",
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"source": [
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"# **FT; Key Information Extraction**\n",
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"Qwen2VLForConditionalGeneration"
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],
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"metadata": {
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"id": "-b4-SW1aGOcF"
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}
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},
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{
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"cell_type": "code",
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"source": [
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"!pip install gradio spaces transformers accelerate numpy requests torch torchvision qwen-vl-utils av ipython reportlab fpdf python-docx pillow huggingface_hub"
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],
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"metadata": {
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"colab": {
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"base_uri": "https://localhost:8080/"
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},
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"id": "oDmd1ZObGSel",
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"outputId": "5b01f267-d5af-4409-cf67-6c318388d584"
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},
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"execution_count": 1,
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"outputs": [
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{
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"output_type": "stream",
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"name": "stdout",
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"text": [
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"Collecting gradio\n",
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" Downloading gradio-5.9.1-py3-none-any.whl.metadata (16 kB)\n",
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"Collecting spaces\n",
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" Downloading spaces-0.31.1-py3-none-any.whl.metadata (1.0 kB)\n",
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"Requirement already satisfied: transformers in /usr/local/lib/python3.10/dist-packages (4.47.1)\n",
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"Requirement already satisfied: accelerate in /usr/local/lib/python3.10/dist-packages (1.2.1)\n",
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"Requirement already satisfied: torch in /usr/local/lib/python3.10/dist-packages (2.5.1+cu121)\n",
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"Requirement already satisfied: torchvision in /usr/local/lib/python3.10/dist-packages (0.20.1+cu121)\n",
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"Collecting qwen-vl-utils\n",
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" Downloading qwen_vl_utils-0.0.8-py3-none-any.whl.metadata (3.6 kB)\n",
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"Collecting av\n",
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" Downloading av-14.0.1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata (4.5 kB)\n",
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"Collecting reportlab\n",
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" Downloading reportlab-4.2.5-py3-none-any.whl.metadata (1.5 kB)\n",
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"Collecting fpdf\n",
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" Downloading fpdf-1.7.2.tar.gz (39 kB)\n",
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" Preparing metadata (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
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"Collecting python-docx\n",
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" Downloading python_docx-1.1.2-py3-none-any.whl.metadata (2.0 kB)\n",
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"Collecting aiofiles<24.0,>=22.0 (from gradio)\n",
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" Building wheel for fpdf (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
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"Installing collected packages: pydub, fpdf, uvicorn, tomlkit, semantic-version, ruff, reportlab, python-multipart, python-docx, markupsafe, jedi, ffmpy, av, aiofiles, starlette, qwen-vl-utils, safehttpx, gradio-client, fastapi, gradio, spaces\n",
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" Found existing installation: MarkupSafe 3.0.2\n",
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" Uninstalling MarkupSafe-3.0.2:\n",
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"Successfully installed aiofiles-23.2.1 av-14.0.1 fastapi-0.115.6 ffmpy-0.5.0 fpdf-1.7.2 gradio-5.9.1 gradio-client-1.5.2 jedi-0.19.2 markupsafe-2.1.5 pydub-0.25.1 python-docx-1.1.2 python-multipart-0.0.20 qwen-vl-utils-0.0.8 reportlab-4.2.5 ruff-0.8.5 safehttpx-0.1.6 semantic-version-2.10.0 spaces-0.31.1 starlette-0.41.3 tomlkit-0.13.2 uvicorn-0.34.0\n"
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{
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"cell_type": "code",
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"source": [
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+
"# Authenticate with Hugging Face\n",
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+
"from huggingface_hub import login\n",
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+
"\n",
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+
"# Log in to Hugging Face using the provided token\n",
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+
"hf_token = '----xxx----'\n",
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+
"login(hf_token)\n",
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+
"\n",
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210 |
+
"#Demo\n",
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+
"import gradio as gr\n",
|
212 |
+
"import spaces\n",
|
213 |
+
"from transformers import Qwen2VLForConditionalGeneration, AutoProcessor, TextIteratorStreamer\n",
|
214 |
+
"from qwen_vl_utils import process_vision_info\n",
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215 |
+
"import torch\n",
|
216 |
+
"from PIL import Image\n",
|
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+
"import os\n",
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+
"import uuid\n",
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+
"import io\n",
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220 |
+
"from threading import Thread\n",
|
221 |
+
"from reportlab.lib.pagesizes import A4\n",
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222 |
+
"from reportlab.lib.styles import getSampleStyleSheet\n",
|
223 |
+
"from reportlab.lib import colors\n",
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224 |
+
"from reportlab.platypus import SimpleDocTemplate, Image as RLImage, Paragraph, Spacer\n",
|
225 |
+
"from reportlab.lib.units import inch\n",
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226 |
+
"from reportlab.pdfbase import pdfmetrics\n",
|
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+
"from reportlab.pdfbase.ttfonts import TTFont\n",
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228 |
+
"import docx\n",
|
229 |
+
"from docx.enum.text import WD_ALIGN_PARAGRAPH\n",
|
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+
"\n",
|
231 |
+
"# Define model options\n",
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+
"MODEL_OPTIONS = {\n",
|
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+
" \"OCR-KIE\": \"prithivMLmods/Qwen2-VL-OCR-2B-Instruct\",\n",
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+
"}\n",
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+
"\n",
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236 |
+
"# Preload models and processors into CUDA\n",
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+
"models = {}\n",
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+
"processors = {}\n",
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239 |
+
"for name, model_id in MODEL_OPTIONS.items():\n",
|
240 |
+
" print(f\"Loading {name}...\")\n",
|
241 |
+
" models[name] = Qwen2VLForConditionalGeneration.from_pretrained(\n",
|
242 |
+
" model_id,\n",
|
243 |
+
" trust_remote_code=True,\n",
|
244 |
+
" torch_dtype=torch.float16\n",
|
245 |
+
" ).to(\"cuda\").eval()\n",
|
246 |
+
" processors[name] = AutoProcessor.from_pretrained(model_id, trust_remote_code=True)\n",
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+
"\n",
|
248 |
+
"image_extensions = Image.registered_extensions()\n",
|
249 |
+
"\n",
|
250 |
+
"def identify_and_save_blob(blob_path):\n",
|
251 |
+
" \"\"\"Identifies if the blob is an image and saves it.\"\"\"\n",
|
252 |
+
" try:\n",
|
253 |
+
" with open(blob_path, 'rb') as file:\n",
|
254 |
+
" blob_content = file.read()\n",
|
255 |
+
" try:\n",
|
256 |
+
" Image.open(io.BytesIO(blob_content)).verify() # Check if it's a valid image\n",
|
257 |
+
" extension = \".png\" # Default to PNG for saving\n",
|
258 |
+
" media_type = \"image\"\n",
|
259 |
+
" except (IOError, SyntaxError):\n",
|
260 |
+
" raise ValueError(\"Unsupported media type. Please upload a valid image.\")\n",
|
261 |
+
"\n",
|
262 |
+
" filename = f\"temp_{uuid.uuid4()}_media{extension}\"\n",
|
263 |
+
" with open(filename, \"wb\") as f:\n",
|
264 |
+
" f.write(blob_content)\n",
|
265 |
+
"\n",
|
266 |
+
" return filename, media_type\n",
|
267 |
+
"\n",
|
268 |
+
" except FileNotFoundError:\n",
|
269 |
+
" raise ValueError(f\"The file {blob_path} was not found.\")\n",
|
270 |
+
" except Exception as e:\n",
|
271 |
+
" raise ValueError(f\"An error occurred while processing the file: {e}\")\n",
|
272 |
+
"\n",
|
273 |
+
"@spaces.GPU\n",
|
274 |
+
"def qwen_inference(model_name, media_input, text_input=None):\n",
|
275 |
+
" \"\"\"Handles inference for the selected model.\"\"\"\n",
|
276 |
+
" model = models[model_name]\n",
|
277 |
+
" processor = processors[model_name]\n",
|
278 |
+
"\n",
|
279 |
+
" if isinstance(media_input, str):\n",
|
280 |
+
" media_path = media_input\n",
|
281 |
+
" if media_path.endswith(tuple([i for i in image_extensions.keys()])):\n",
|
282 |
+
" media_type = \"image\"\n",
|
283 |
+
" else:\n",
|
284 |
+
" try:\n",
|
285 |
+
" media_path, media_type = identify_and_save_blob(media_input)\n",
|
286 |
+
" except Exception as e:\n",
|
287 |
+
" raise ValueError(\"Unsupported media type. Please upload a valid image.\")\n",
|
288 |
+
"\n",
|
289 |
+
" messages = [\n",
|
290 |
+
" {\n",
|
291 |
+
" \"role\": \"user\",\n",
|
292 |
+
" \"content\": [\n",
|
293 |
+
" {\n",
|
294 |
+
" \"type\": media_type,\n",
|
295 |
+
" media_type: media_path\n",
|
296 |
+
" },\n",
|
297 |
+
" {\"type\": \"text\", \"text\": text_input},\n",
|
298 |
+
" ],\n",
|
299 |
+
" }\n",
|
300 |
+
" ]\n",
|
301 |
+
"\n",
|
302 |
+
" text = processor.apply_chat_template(\n",
|
303 |
+
" messages, tokenize=False, add_generation_prompt=True\n",
|
304 |
+
" )\n",
|
305 |
+
" image_inputs, _ = process_vision_info(messages)\n",
|
306 |
+
" inputs = processor(\n",
|
307 |
+
" text=[text],\n",
|
308 |
+
" images=image_inputs,\n",
|
309 |
+
" padding=True,\n",
|
310 |
+
" return_tensors=\"pt\",\n",
|
311 |
+
" ).to(\"cuda\")\n",
|
312 |
+
"\n",
|
313 |
+
" streamer = TextIteratorStreamer(\n",
|
314 |
+
" processor.tokenizer, skip_prompt=True, skip_special_tokens=True\n",
|
315 |
+
" )\n",
|
316 |
+
" generation_kwargs = dict(inputs, streamer=streamer, max_new_tokens=1024)\n",
|
317 |
+
"\n",
|
318 |
+
" thread = Thread(target=model.generate, kwargs=generation_kwargs)\n",
|
319 |
+
" thread.start()\n",
|
320 |
+
"\n",
|
321 |
+
" buffer = \"\"\n",
|
322 |
+
" for new_text in streamer:\n",
|
323 |
+
" buffer += new_text\n",
|
324 |
+
" # Remove <|im_end|> or similar tokens from the output\n",
|
325 |
+
" buffer = buffer.replace(\"<|im_end|>\", \"\")\n",
|
326 |
+
" yield buffer\n",
|
327 |
+
"\n",
|
328 |
+
"def format_plain_text(output_text):\n",
|
329 |
+
" \"\"\"Formats the output text as plain text without LaTeX delimiters.\"\"\"\n",
|
330 |
+
" # Remove LaTeX delimiters and convert to plain text\n",
|
331 |
+
" plain_text = output_text.replace(\"\\\\(\", \"\").replace(\"\\\\)\", \"\").replace(\"\\\\[\", \"\").replace(\"\\\\]\", \"\")\n",
|
332 |
+
" return plain_text\n",
|
333 |
+
"\n",
|
334 |
+
"def generate_document(media_path, output_text, file_format, font_size, line_spacing, alignment, image_size):\n",
|
335 |
+
" \"\"\"Generates a document with the input image and plain text output.\"\"\"\n",
|
336 |
+
" plain_text = format_plain_text(output_text)\n",
|
337 |
+
" if file_format == \"pdf\":\n",
|
338 |
+
" return generate_pdf(media_path, plain_text, font_size, line_spacing, alignment, image_size)\n",
|
339 |
+
" elif file_format == \"docx\":\n",
|
340 |
+
" return generate_docx(media_path, plain_text, font_size, line_spacing, alignment, image_size)\n",
|
341 |
+
"\n",
|
342 |
+
"def generate_pdf(media_path, plain_text, font_size, line_spacing, alignment, image_size):\n",
|
343 |
+
" \"\"\"Generates a PDF document.\"\"\"\n",
|
344 |
+
" filename = f\"output_{uuid.uuid4()}.pdf\"\n",
|
345 |
+
" doc = SimpleDocTemplate(\n",
|
346 |
+
" filename,\n",
|
347 |
+
" pagesize=A4,\n",
|
348 |
+
" rightMargin=inch,\n",
|
349 |
+
" leftMargin=inch,\n",
|
350 |
+
" topMargin=inch,\n",
|
351 |
+
" bottomMargin=inch\n",
|
352 |
+
" )\n",
|
353 |
+
" styles = getSampleStyleSheet()\n",
|
354 |
+
" styles[\"Normal\"].fontSize = int(font_size)\n",
|
355 |
+
" styles[\"Normal\"].leading = int(font_size) * line_spacing\n",
|
356 |
+
" styles[\"Normal\"].alignment = {\n",
|
357 |
+
" \"Left\": 0,\n",
|
358 |
+
" \"Center\": 1,\n",
|
359 |
+
" \"Right\": 2,\n",
|
360 |
+
" \"Justified\": 4\n",
|
361 |
+
" }[alignment]\n",
|
362 |
+
"\n",
|
363 |
+
" story = []\n",
|
364 |
+
"\n",
|
365 |
+
" # Add image with size adjustment\n",
|
366 |
+
" image_sizes = {\n",
|
367 |
+
" \"Small\": (200, 200),\n",
|
368 |
+
" \"Medium\": (400, 400),\n",
|
369 |
+
" \"Large\": (600, 600)\n",
|
370 |
+
" }\n",
|
371 |
+
" img = RLImage(media_path, width=image_sizes[image_size][0], height=image_sizes[image_size][1])\n",
|
372 |
+
" story.append(img)\n",
|
373 |
+
" story.append(Spacer(1, 12))\n",
|
374 |
+
"\n",
|
375 |
+
" # Add plain text output\n",
|
376 |
+
" text = Paragraph(plain_text, styles[\"Normal\"])\n",
|
377 |
+
" story.append(text)\n",
|
378 |
+
"\n",
|
379 |
+
" doc.build(story)\n",
|
380 |
+
" return filename\n",
|
381 |
+
"\n",
|
382 |
+
"def generate_docx(media_path, plain_text, font_size, line_spacing, alignment, image_size):\n",
|
383 |
+
" \"\"\"Generates a DOCX document.\"\"\"\n",
|
384 |
+
" filename = f\"output_{uuid.uuid4()}.docx\"\n",
|
385 |
+
" doc = docx.Document()\n",
|
386 |
+
"\n",
|
387 |
+
" # Add image with size adjustment\n",
|
388 |
+
" image_sizes = {\n",
|
389 |
+
" \"Small\": docx.shared.Inches(2),\n",
|
390 |
+
" \"Medium\": docx.shared.Inches(4),\n",
|
391 |
+
" \"Large\": docx.shared.Inches(6)\n",
|
392 |
+
" }\n",
|
393 |
+
" doc.add_picture(media_path, width=image_sizes[image_size])\n",
|
394 |
+
" doc.add_paragraph()\n",
|
395 |
+
"\n",
|
396 |
+
" # Add plain text output\n",
|
397 |
+
" paragraph = doc.add_paragraph()\n",
|
398 |
+
" paragraph.paragraph_format.line_spacing = line_spacing\n",
|
399 |
+
" paragraph.paragraph_format.alignment = {\n",
|
400 |
+
" \"Left\": WD_ALIGN_PARAGRAPH.LEFT,\n",
|
401 |
+
" \"Center\": WD_ALIGN_PARAGRAPH.CENTER,\n",
|
402 |
+
" \"Right\": WD_ALIGN_PARAGRAPH.RIGHT,\n",
|
403 |
+
" \"Justified\": WD_ALIGN_PARAGRAPH.JUSTIFY\n",
|
404 |
+
" }[alignment]\n",
|
405 |
+
" run = paragraph.add_run(plain_text)\n",
|
406 |
+
" run.font.size = docx.shared.Pt(int(font_size))\n",
|
407 |
+
"\n",
|
408 |
+
" doc.save(filename)\n",
|
409 |
+
" return filename\n",
|
410 |
+
"\n",
|
411 |
+
"# CSS for output styling\n",
|
412 |
+
"css = \"\"\"\n",
|
413 |
+
" #output {\n",
|
414 |
+
" height: 500px;\n",
|
415 |
+
" overflow: auto;\n",
|
416 |
+
" border: 1px solid #ccc;\n",
|
417 |
+
" }\n",
|
418 |
+
".submit-btn {\n",
|
419 |
+
" background-color: #cf3434 !important;\n",
|
420 |
+
" color: white !important;\n",
|
421 |
+
"}\n",
|
422 |
+
".submit-btn:hover {\n",
|
423 |
+
" background-color: #ff2323 !important;\n",
|
424 |
+
"}\n",
|
425 |
+
".download-btn {\n",
|
426 |
+
" background-color: #35a6d6 !important;\n",
|
427 |
+
" color: white !important;\n",
|
428 |
+
"}\n",
|
429 |
+
".download-btn:hover {\n",
|
430 |
+
" background-color: #22bcff !important;\n",
|
431 |
+
"}\n",
|
432 |
+
"\"\"\"\n",
|
433 |
+
"\n",
|
434 |
+
"# Gradio app setup\n",
|
435 |
+
"with gr.Blocks(css=css) as demo:\n",
|
436 |
+
" gr.Markdown(\"# Qwen2VL Models: Vision and Language Processing\")\n",
|
437 |
+
"\n",
|
438 |
+
" with gr.Tab(label=\"Image Input\"):\n",
|
439 |
+
"\n",
|
440 |
+
" with gr.Row():\n",
|
441 |
+
" with gr.Column():\n",
|
442 |
+
" model_choice = gr.Dropdown(\n",
|
443 |
+
" label=\"Model Selection\",\n",
|
444 |
+
" choices=list(MODEL_OPTIONS.keys()),\n",
|
445 |
+
" value=\"OCR-KIE\"\n",
|
446 |
+
" )\n",
|
447 |
+
" input_media = gr.File(\n",
|
448 |
+
" label=\"Upload Image\", type=\"filepath\"\n",
|
449 |
+
" )\n",
|
450 |
+
" text_input = gr.Textbox(label=\"Question\", placeholder=\"Ask a question about the image...\")\n",
|
451 |
+
" submit_btn = gr.Button(value=\"Submit\", elem_classes=\"submit-btn\")\n",
|
452 |
+
"\n",
|
453 |
+
" with gr.Column():\n",
|
454 |
+
" output_text = gr.Textbox(label=\"Output Text\", lines=10)\n",
|
455 |
+
" plain_text_output = gr.Textbox(label=\"Standardized Plain Text\", lines=10)\n",
|
456 |
+
"\n",
|
457 |
+
" submit_btn.click(\n",
|
458 |
+
" qwen_inference, [model_choice, input_media, text_input], [output_text]\n",
|
459 |
+
" ).then(\n",
|
460 |
+
" lambda output_text: format_plain_text(output_text), [output_text], [plain_text_output]\n",
|
461 |
+
" )\n",
|
462 |
+
"\n",
|
463 |
+
" # Add examples directly usable by clicking\n",
|
464 |
+
" with gr.Row():\n",
|
465 |
+
" with gr.Column():\n",
|
466 |
+
" line_spacing = gr.Dropdown(\n",
|
467 |
+
" choices=[0.5, 1.0, 1.15, 1.5, 2.0, 2.5, 3.0],\n",
|
468 |
+
" value=1.5,\n",
|
469 |
+
" label=\"Line Spacing\"\n",
|
470 |
+
" )\n",
|
471 |
+
" font_size = gr.Dropdown(\n",
|
472 |
+
" choices=[\"8\", \"10\", \"12\", \"14\", \"16\", \"18\", \"20\", \"22\", \"24\"],\n",
|
473 |
+
" value=\"18\",\n",
|
474 |
+
" label=\"Font Size\"\n",
|
475 |
+
" )\n",
|
476 |
+
" alignment = gr.Dropdown(\n",
|
477 |
+
" choices=[\"Left\", \"Center\", \"Right\", \"Justified\"],\n",
|
478 |
+
" value=\"Justified\",\n",
|
479 |
+
" label=\"Text Alignment\"\n",
|
480 |
+
" )\n",
|
481 |
+
" image_size = gr.Dropdown(\n",
|
482 |
+
" choices=[\"Small\", \"Medium\", \"Large\"],\n",
|
483 |
+
" value=\"Small\",\n",
|
484 |
+
" label=\"Image Size\"\n",
|
485 |
+
" )\n",
|
486 |
+
" file_format = gr.Radio([\"pdf\", \"docx\"], label=\"File Format\", value=\"pdf\")\n",
|
487 |
+
" get_document_btn = gr.Button(value=\"Get Document\", elem_classes=\"download-btn\")\n",
|
488 |
+
"\n",
|
489 |
+
" get_document_btn.click(\n",
|
490 |
+
" generate_document, [input_media, output_text, file_format, font_size, line_spacing, alignment, image_size], gr.File(label=\"Download Document\")\n",
|
491 |
+
" )\n",
|
492 |
+
"\n",
|
493 |
+
"demo.launch(debug=True)"
|
494 |
+
],
|
495 |
+
"metadata": {
|
496 |
+
"colab": {
|
497 |
+
"base_uri": "https://localhost:8080/",
|
498 |
+
"height": 715
|
499 |
+
},
|
500 |
+
"id": "ovBSsRFhGbs2",
|
501 |
+
"outputId": "2a5bc724-4eab-4167-9c52-b378ce3799e3"
|
502 |
+
},
|
503 |
+
"execution_count": 4,
|
504 |
+
"outputs": [
|
505 |
+
{
|
506 |
+
"output_type": "stream",
|
507 |
+
"name": "stderr",
|
508 |
+
"text": [
|
509 |
+
"The argument `trust_remote_code` is to be used with Auto classes. It has no effect here and is ignored.\n"
|
510 |
+
]
|
511 |
+
},
|
512 |
+
{
|
513 |
+
"output_type": "stream",
|
514 |
+
"name": "stdout",
|
515 |
+
"text": [
|
516 |
+
"Loading OCR-KIE...\n",
|
517 |
+
"Running Gradio in a Colab notebook requires sharing enabled. Automatically setting `share=True` (you can turn this off by setting `share=False` in `launch()` explicitly).\n",
|
518 |
+
"\n",
|
519 |
+
"Colab notebook detected. This cell will run indefinitely so that you can see errors and logs. To turn off, set debug=False in launch().\n",
|
520 |
+
"* Running on public URL: https://49b22c4dd53a6ec06e.gradio.live\n",
|
521 |
+
"\n",
|
522 |
+
"This share link expires in 72 hours. For free permanent hosting and GPU upgrades, run `gradio deploy` from the terminal in the working directory to deploy to Hugging Face Spaces (https://huggingface.co/spaces)\n"
|
523 |
+
]
|
524 |
+
},
|
525 |
+
{
|
526 |
+
"output_type": "display_data",
|
527 |
+
"data": {
|
528 |
+
"text/plain": [
|
529 |
+
"<IPython.core.display.HTML object>"
|
530 |
+
],
|
531 |
+
"text/html": [
|
532 |
+
"<div><iframe src=\"https://49b22c4dd53a6ec06e.gradio.live\" width=\"100%\" height=\"500\" allow=\"autoplay; camera; microphone; clipboard-read; clipboard-write;\" frameborder=\"0\" allowfullscreen></iframe></div>"
|
533 |
+
]
|
534 |
+
},
|
535 |
+
"metadata": {}
|
536 |
+
},
|
537 |
+
{
|
538 |
+
"output_type": "stream",
|
539 |
+
"name": "stdout",
|
540 |
+
"text": [
|
541 |
+
"Keyboard interruption in main thread... closing server.\n",
|
542 |
+
"Killing tunnel 127.0.0.1:7860 <> https://49b22c4dd53a6ec06e.gradio.live\n"
|
543 |
+
]
|
544 |
+
},
|
545 |
+
{
|
546 |
+
"output_type": "execute_result",
|
547 |
+
"data": {
|
548 |
+
"text/plain": []
|
549 |
+
},
|
550 |
+
"metadata": {},
|
551 |
+
"execution_count": 4
|
552 |
+
}
|
553 |
+
]
|
554 |
+
}
|
555 |
+
]
|
556 |
+
}
|