feat: Update dockerfile

fix: form with multi-part python, np format for model
feat: Add app
2025-08-18 08:06:51 +00:00 · 2025-08-17 14:12:26 +00:00 · 2025-08-17 13:28:25 +00:00 · 2025-08-16 21:16:58 +00:00
8 changed files with 520 additions and 71 deletions
--- a/.gitignore
+++ b/.gitignore
@@ -147,3 +147,4 @@ tmp/
 data/

 *.pth
+temp_dir/
--- a/39
+++ b/39
@@ -1,35 +1,28 @@
-FROM pytorch/pytorch:2.1.2-cuda12.1-cudnn8-runtime
+FROM pytorch/pytorch:2.8.0-cuda12.6-cudnn9-runtime
 ARG DEBIAN_FRONTEND=noninteractive

 ENV CUDA_HOME=/usr/local/cuda \
-     TORCH_CUDA_ARCH_LIST="6.0 6.1 7.0 7.5 8.0 8.6+PTX" \
-     SETUPTOOLS_USE_DISTUTILS=stdlib
+     TORCH_CUDA_ARCH_LIST="6.0 6.1 7.0 7.5 8.0 8.6+PTX"

-RUN conda update conda -y
+# RUN conda update conda -y

-# Install libraries in the brand new image. 
-RUN apt-get -y update && apt-get install -y --no-install-recommends \
-         wget \
-         build-essential \
-         git \
-         python3-opencv \
-         ca-certificates && \
-    rm -rf /var/lib/apt/lists/*
+RUN apt -y update && apt install tesseract-ocr -y
+RUN apt-get -y update && apt-get install libgl1 poppler-utils -y --no-install-recommends

 # Set the working directory for all the subsequent Dockerfile instructions.
-WORKDIR /opt/program
-
-RUN git clone https://github.com/IDEA-Research/GroundingDINO.git
+WORKDIR /app

 RUN mkdir weights ; cd weights ; wget -q https://github.com/IDEA-Research/GroundingDINO/releases/download/v0.1.0-alpha/groundingdino_swint_ogc.pth ; cd ..

-RUN conda install -c "nvidia/label/cuda-12.1.1" cuda -y
-ENV CUDA_HOME=$CONDA_PREFIX
+COPY app.py /app/
+COPY pdf_converter.py /app/
+COPY uv.lock /app/
+COPY setup.py /app/
+ADD groundingdino/ /app/groundingdino/
+COPY pyproject.toml /app/

-ENV PATH=/usr/local/cuda/bin:$PATH
+# RUN cd GroundingDINO/ && python -m pip install .
+RUN pip install --no-cache-dir uv && uv sync --no-cache
+RUN /app/.venv/bin/python -m pip install -e .

-RUN cd GroundingDINO/ && python -m pip install .
-
-COPY docker_test.py docker_test.py
-
-CMD [ "python", "docker_test.py" ]
+CMD [ "/app/.venv/bin/python", "app.py" ]
--- a/app.py
+++ b/app.py
@@ -0,0 +1,192 @@
+import os
+import uuid
+from io import BytesIO
+from pathlib import Path
+from typing import Literal, Optional
+import base64
+
+import numpy as np
+import supervision as sv
+import uvicorn
+import yaml
+from fastapi import (FastAPI, File, Form, HTTPException, Query, Request,
+                     UploadFile)
+from fastapi.middleware.cors import CORSMiddleware
+from fastapi.responses import JSONResponse
+from fastapi.security.api_key import APIKeyHeader
+from PIL import Image
+from starlette.status import HTTP_403_FORBIDDEN
+
+from groundingdino.util.inference import Model, preprocess_caption
+from pdf_converter import PdfConverter
+
+PROCESSED_FOLDER = Path(os.environ.get("TEMP_IMG_FOLDER", "temp_dir"))
+PROCESSED_FOLDER.mkdir(parents=True, exist_ok=True)
+BASE_URL = "http://127.0.0.1:8000"
+
+API_PARTNER_KEY = os.environ.get("API_PARTNER_KEY", "dev-AfghDgr3fgf74vc")
+API_KEY_NAME = "x-api-key"
+api_key_header = APIKeyHeader(name=API_KEY_NAME, auto_error=False)
+
+app = FastAPI()
+
+app.add_middleware(
+    CORSMiddleware,
+    allow_origins=["*"],
+    allow_credentials=True,
+    allow_methods=["*"],
+    allow_headers=["*"],
+)
+
+pdf_converter: PdfConverter = PdfConverter(dpi=150)
+grounding_model = Model(
+    model_config_path=os.environ.get(
+        "GROUNDING_DINO_CONFIG", "groundingdino/config/GroundingDINO_SwinT_OGC.py"
+    ),
+    model_checkpoint_path=os.environ.get(
+        "GROUNDING_DINO_CHECKPOINT", "gdino_checkpoints/groundingdino_swint_ogc.pth"
+    ),
+    device="cuda:0",
+)
+BOX_THRESHOLD = 0.4
+TEXT_THRESHOLD = 0.25
+
+
+def output_img(processed_img: Image,output: Literal["url", "base64"]) -> dict[str, any]:
+    if output == "url":
+        unique_filename = f"{uuid.uuid4()}.png"
+        save_path = os.path.join(PROCESSED_FOLDER, unique_filename)
+        # Save the processed image to the filesystem
+        processed_img.save(save_path, 'PNG')
+        # Construct the full URL for the client to access the image
+        # request.base_url gives us the root path (e.g., http://127.0.0.1:8000/)
+        image_url = f"{BASE_URL}/{PROCESSED_FOLDER}/{unique_filename}"
+        image_json = {
+            "image": image_url,
+            "metadata": {
+                "type": "url",
+                "format": "png",
+                "width": processed_img.width,
+                "height": processed_img.height,
+                "mode": processed_img.mode,
+            },
+        }
+        return image_json
+    elif output == 'base64':
+        # Save the image to an in-memory buffer instead of a file
+        buffered = BytesIO()
+        processed_img.save(buffered, format="PNG")
+        # Encode the bytes to a Base64 string
+        img_str = base64.b64encode(buffered.getvalue()).decode("utf-8")
+        # Prepend the data URI scheme
+        base64_data_uri = f"data:image/png;base64,{img_str}"
+        image_json = {
+            "image": base64_data_uri,
+            "metadata": {
+                "type": "base64",
+                "format": "png",
+                "width": processed_img.width,
+                "height": processed_img.height,
+                "mode": processed_img.mode,
+            },
+        }
+        return image_json
+
+
+async def verify_api_key(request: Request):
+    api_key = await api_key_header(request)
+    if API_PARTNER_KEY is None or api_key != API_PARTNER_KEY:
+        raise HTTPException(
+            status_code=HTTP_403_FORBIDDEN,
+            detail="Could not validate API KEY",
+        )
+
+
+@app.middleware("http")
+async def api_key_middleware(request: Request, call_next):
+    # Allow docs and openapi without API key
+    if request.url.path in ["/docs", "/openapi.json", "/redoc"]:
+        return await call_next(request)
+    try:
+        await verify_api_key(request)
+    except HTTPException as exc:
+        return JSONResponse(status_code=exc.status_code, content={"detail": exc.detail})
+    return await call_next(request)
+
+
+@app.post("/crop_ooi")
+async def crop_object_of_interest(
+    document_file: UploadFile = File(
+        ..., description="The document to process."
+    ),
+    concept_list: Optional[list[str]] = Form(
+        ["ID document"], description="List of concepts to detect e.g. dog, cat, rain"
+    ),
+    box_threshold: Optional[float] = Form(
+        0.4, description="Threshold rate to keep confidence detections"
+    ),
+    text_threshold: Optional[float] = Form(0.25, description="Text threshold"),
+    output: Literal["url", "base64"] = Query(
+        "base64", description="The desired output format."
+    ),
+    render_detection: Optional[bool] = Form(
+        False,
+        description="True if the output contains picture with detected objects with bboxes",
+    ),
+):
+    content = await document_file.read()
+    if document_file.content_type not in ["application/pdf", "image/jpeg", "image/png"]:
+        raise HTTPException(
+            status_code=400,
+            detail=f"Unsupported file type ({document_file.content_type}).",
+        )
+    try:
+        images = pdf_converter.convert_pdf_bytes_to_jpg(content)
+        text = "".join([f"{x}. " for x in concept_list])
+        caption = preprocess_caption(text)
+        image_list = []
+        detection_img_list = []
+        for image in images:
+            detections, labels = grounding_model.predict_with_caption(
+                image=np.asarray(image),
+                caption=caption,
+                box_threshold=box_threshold,
+                text_threshold=text_threshold,
+            )
+            confidences = detections.confidence.tolist()
+            class_names = labels
+
+            labels = [
+                f"{class_name} {confidence:.2f}"
+                for class_name, confidence in zip(class_names, confidences)
+            ]
+            for i, bbox in enumerate(detections.xyxy):
+                x_min, y_min, x_max, y_max = tuple(bbox)
+                patch = image.crop((int(y_min), int(y_max), int(x_min), int(x_max)))
+                image_json = output_img(processed_img=patch, output=output)
+                image_list.append(image_json)
+
+            if render_detection:
+                box_annotator = sv.BoxAnnotator(color_lookup=sv.ColorLookup.INDEX)
+                annotated_frame = box_annotator.annotate(
+                    scene=image.copy(), detections=detections
+                )
+                label_annotator = sv.LabelAnnotator(color_lookup=sv.ColorLookup.INDEX)
+                annotated_frame = label_annotator.annotate(
+                    scene=annotated_frame, detections=detections, labels=labels
+                )
+                detection_image_json = output_img(processed_img=annotated_frame, output=output)
+                detection_img_list.append(detection_image_json)
+
+        response_data = dict(status="succes", images=image_list)
+        return JSONResponse(status_code=200, content=response_data)
+
+    except Exception as e:
+        print(f"{e}")
+        return JSONResponse(status_code=501, content=str(e))
+
+
+if __name__ == "__main__":
+    APP_PORT = int(os.environ.get("APP_PORT", 8000))
+    APP_HOST = os.environ.get("APP_HOST", "0.0.0.0")
+    uvicorn.run(app, host=APP_HOST, port=APP_PORT)
--- a/main.py
+++ b/main.py
@@ -1,15 +1,13 @@
 from pathlib import Path

 import cv2
-import numpy as np
 import supervision as sv
 import torch
 import yaml
-from pdf2image import convert_from_bytes, convert_from_path
-from PIL import Image
 from tqdm import tqdm

 from groundingdino.util.inference import Model, preprocess_caption
+from pdf_converter import PdfConverter

 GROUNDING_DINO_CONFIG = "groundingdino/config/GroundingDINO_SwinT_OGC.py"
 GROUNDING_DINO_CHECKPOINT = "gdino_checkpoints/groundingdino_swint_ogc.pth"
@@ -17,49 +15,6 @@ BOX_THRESHOLD = 0.4
 TEXT_THRESHOLD = 0.25


-class PdfConverterService:
-    """
-    A service to convert PDF files to images and resize images,
-    using pypdfium2 for PDFs and Pillow for images.
-    """
-
-    def __init__(self, dpi: int):
-        self._pdfium_initialized = False  # Track if PDFium needs explicit init/deinit
-        self._dpi = dpi
-
-    def convert_pdf_to_jpg(self, file_path: str) -> list[Image.Image]:
-        """
-        Converts a PDF file to JPG images at different scales.
-        """
-        pil_images = convert_from_path(file_path, dpi=self._dpi)
-        return pil_images
-
-    def resize_image(self, img: Image.Image, size: tuple[int, int]) -> Image.Image:
-        """
-        Resizes a PIL Image to the specified size.
-        """
-        return img.resize(size, Image.LANCZOS)
-
-    @staticmethod
-    def save_image_as_png(img: Image.Image, file_path: str):
-        """
-        Saves a PIL Image as a PNG file.
-        """
-        img.save(file_path, format="PNG")
-
-    @staticmethod
-    def to_cv2_image(img: Image.Image):
-        open_cv_image = np.array(img.convert("RGB"))
-        return open_cv_image[:, :, ::-1].copy()
-
-    def convert_pdf_bytes_to_jpg(self, pdf_bytes: bytes) -> list[Image.Image]:
-        """
-        Converts PDF bytes to JPG images at different scales.
-        """
-        pil_images = convert_from_bytes(pdf_bytes, dpi=self._dpi)
-        return pil_images
-
-
 def main(
    data_dir: str | Path,
    text: str = "ID card. Carte Vitale. Bank details. Human face.",
@@ -82,7 +37,7 @@ def main(
    for img_path in tqdm(
        data_dir.glob("*.pdf"), total=len(list(data_dir.glob("*.pdf")))
    ):
-        pdf_convertor = PdfConverterService(120)
+        pdf_convertor = PdfConverter(120)
        if img_path.suffix == ".pdf":
            imgs = pdf_convertor.convert_pdf_to_jpg(str(img_path))
            img = imgs[0]
--- a/pdf_converter.py
+++ b/pdf_converter.py
@@ -0,0 +1,46 @@
+import numpy as np
+from pdf2image import convert_from_bytes, convert_from_path
+from PIL import Image
+
+
+class PdfConverter:
+    """
+    A service to convert PDF files to images and resize images,
+    using pypdfium2 for PDFs and Pillow for images.
+    """
+
+    def __init__(self, dpi: int):
+        self._pdfium_initialized = False  # Track if PDFium needs explicit init/deinit
+        self._dpi = dpi
+
+    def convert_pdf_to_jpg(self, file_path: str) -> list[Image.Image]:
+        """
+        Converts a PDF file to JPG images at different scales.
+        """
+        pil_images = convert_from_path(file_path, dpi=self._dpi)
+        return pil_images
+
+    def resize_image(self, img: Image.Image, size: tuple[int, int]) -> Image.Image:
+        """
+        Resizes a PIL Image to the specified size.
+        """
+        return img.resize(size, Image.LANCZOS)
+
+    @staticmethod
+    def save_image_as_png(img: Image.Image, file_path: str):
+        """
+        Saves a PIL Image as a PNG file.
+        """
+        img.save(file_path, format="PNG")
+
+    @staticmethod
+    def to_cv2_image(img: Image.Image):
+        open_cv_image = np.array(img.convert("RGB"))
+        return open_cv_image[:, :, ::-1].copy()
+
+    def convert_pdf_bytes_to_jpg(self, pdf_bytes: bytes) -> list[Image.Image]:
+        """
+        Converts PDF bytes to JPG images at different scales.
+        """
+        pil_images = convert_from_bytes(pdf_bytes, dpi=self._dpi)
+        return pil_images
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -22,4 +22,9 @@ dependencies = [
    "pdf2image>=1.17.0",
    "pip>=25.2",
    "setuptools>=80.9.0",
+    "uvicorn>=0.35.0",
+    "fastapi>=0.116.1",
+    "openai>=1.99.9",
+    "starlette>=0.47.2",
+    "python-multipart>=0.0.20",
 ]
--- a/setup.py
+++ b/setup.py
@@ -38,7 +38,7 @@ def install_torch():
 # Call the function to ensure torch is installed
 # install_torch()
 sys.path.insert(
-    0, "/home/nguyendc/cuong-dev/GroundingDINO/.venv/lib/python3.13/site-packages"
+    0, f"{__file__}/.venv/lib/python3.13/site-packages"
 )

 import torch
--- a/uv.lock
+++ b/uv.lock
@@ -16,12 +16,34 @@ wheels = [
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 ]

+[[package]]
+name = "annotated-types"
+version = "0.7.0"
+source = { registry = "https://pypi.org/simple" }
+sdist = { url = "https://files.pythonhosted.org/packages/ee/67/531ea369ba64dcff5ec9c3402f9f51bf748cec26dde048a2f973a4eea7f5/annotated_types-0.7.0.tar.gz", hash = "sha256:aff07c09a53a08bc8cfccb9c85b05f1aa9a2a6f23728d790723543408344ce89", size = 16081, upload-time = "2024-05-20T21:33:25.928Z" }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/78/b6/6307fbef88d9b5ee7421e68d78a9f162e0da4900bc5f5793f6d3d0e34fb8/annotated_types-0.7.0-py3-none-any.whl", hash = "sha256:1f02e8b43a8fbbc3f3e0d4f0f4bfc8131bcb4eebe8849b8e5c773f3a1c582a53", size = 13643, upload-time = "2024-05-20T21:33:24.1Z" },
+]
+
 [[package]]
 name = "antlr4-python3-runtime"
 version = "4.9.3"
 source = { registry = "https://pypi.org/simple" }
 sdist = { url = "https://files.pythonhosted.org/packages/3e/38/7859ff46355f76f8d19459005ca000b6e7012f2f1ca597746cbcd1fbfe5e/antlr4-python3-runtime-4.9.3.tar.gz", hash = "sha256:f224469b4168294902bb1efa80a8bf7855f24c99aef99cbefc1bcd3cce77881b", size = 117034, upload-time = "2021-11-06T17:52:23.524Z" }

+[[package]]
+name = "anyio"
+version = "4.10.0"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "idna" },
+    { name = "sniffio" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/f1/b4/636b3b65173d3ce9a38ef5f0522789614e590dab6a8d505340a4efe4c567/anyio-4.10.0.tar.gz", hash = "sha256:3f3fae35c96039744587aa5b8371e7e8e603c0702999535961dd336026973ba6", size = 213252, upload-time = "2025-08-04T08:54:26.451Z" }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/6f/12/e5e0282d673bb9746bacfb6e2dba8719989d3660cdb2ea79aee9a9651afb/anyio-4.10.0-py3-none-any.whl", hash = "sha256:60e474ac86736bbfd6f210f7a61218939c318f43f9972497381f1c5e930ed3d1", size = 107213, upload-time = "2025-08-04T08:54:24.882Z" },
+]
+
 [[package]]
 name = "certifi"
 version = "2025.8.3"
@@ -62,6 +84,18 @@ wheels = [
    { url = "https://files.pythonhosted.org/packages/8a/1f/f041989e93b001bc4e44bb1669ccdcf54d3f00e628229a85b08d330615c5/charset_normalizer-3.4.3-py3-none-any.whl", hash = "sha256:ce571ab16d890d23b5c278547ba694193a45011ff86a9162a71307ed9f86759a", size = 53175, upload-time = "2025-08-09T07:57:26.864Z" },
 ]

+[[package]]
+name = "click"
+version = "8.2.1"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "colorama", marker = "sys_platform == 'win32'" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/60/6c/8ca2efa64cf75a977a0d7fac081354553ebe483345c734fb6b6515d96bbc/click-8.2.1.tar.gz", hash = "sha256:27c491cc05d968d271d5a1db13e3b5a184636d9d930f148c50b038f0d0646202", size = 286342, upload-time = "2025-05-20T23:19:49.832Z" }
+wheels = [
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+]
+
 [[package]]
 name = "colorama"
 version = "0.4.6"
@@ -144,6 +178,29 @@ wheels = [
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 ]

+[[package]]
+name = "distro"
+version = "1.9.0"
+source = { registry = "https://pypi.org/simple" }
+sdist = { url = "https://files.pythonhosted.org/packages/fc/f8/98eea607f65de6527f8a2e8885fc8015d3e6f5775df186e443e0964a11c3/distro-1.9.0.tar.gz", hash = "sha256:2fa77c6fd8940f116ee1d6b94a2f90b13b5ea8d019b98bc8bafdcabcdd9bdbed", size = 60722, upload-time = "2023-12-24T09:54:32.31Z" }
+wheels = [
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+]
+
+[[package]]
+name = "fastapi"
+version = "0.116.1"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "pydantic" },
+    { name = "starlette" },
+    { name = "typing-extensions" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/78/d7/6c8b3bfe33eeffa208183ec037fee0cce9f7f024089ab1c5d12ef04bd27c/fastapi-0.116.1.tar.gz", hash = "sha256:ed52cbf946abfd70c5a0dccb24673f0670deeb517a88b3544d03c2a6bf283143", size = 296485, upload-time = "2025-07-11T16:22:32.057Z" }
+wheels = [
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+]
+
 [[package]]
 name = "filelock"
 version = "3.19.1"
@@ -201,45 +258,64 @@ version = "0.1.0"
 source = { virtual = "." }
 dependencies = [
    { name = "addict" },
+    { name = "fastapi" },
    { name = "hydra-core" },
    { name = "iopath" },
    { name = "numpy" },
+    { name = "openai" },
    { name = "opencv-python-headless" },
    { name = "pdf2image" },
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Author	SHA1	Message	Date
kiennt	83c93e85ac	feat: Update dockerfile	2025-08-18 08:06:51 +00:00
kiennt	e09128f94c	fix: form with multi-part python, np format for model	2025-08-17 14:12:26 +00:00
kiennt	147c52de71	feat: Add app	2025-08-17 13:28:25 +00:00
kiennt	e3f3ab95cc	feat: Add app	2025-08-16 21:16:58 +00:00