add all

.dockerignore

@@ -0,0 +1,138 @@
+# Byte-compiled / optimized / DLL files
+__pycache__/
+*.py[cod]
+*$py.class
+
+# C extensions
+*.so
+
+# Distribution / packaging
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+pip-wheel-metadata/
+share/python-wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+MANIFEST
+
+# PyInstaller
+#  Usually these files are written by a python script from a template
+#  before PyInstaller builds the exe, so as to inject date/other infos into it.
+*.manifest
+*.spec
+
+# Installer logs
+pip-log.txt
+pip-delete-this-directory.txt
+
+# Unit test / coverage reports
+htmlcov/
+.tox/
+.nox/
+.coverage
+.coverage.*
+.cache
+nosetests.xml
+coverage.xml
+*.cover
+*.py,cover
+.hypothesis/
+.pytest_cache/
+
+# Translations
+*.mo
+*.pot
+
+# Django stuff:
+*.log
+local_settings.py
+db.sqlite3
+db.sqlite3-journal
+
+# Flask stuff:
+instance/
+.webassets-cache
+
+# Scrapy stuff:
+.scrapy
+
+# Sphinx documentation
+docs/_build/
+
+# PyBuilder
+target/
+
+# Jupyter Notebook
+.ipynb_checkpoints
+
+# IPython
+profile_default/
+ipython_config.py
+
+# pyenv
+.python-version
+
+# pipenv
+#   According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
+#   However, in case of collaboration, if having platform-specific dependencies or dependencies
+#   having no cross-platform support, pipenv may install dependencies that don't work, or not
+#   install all needed dependencies.
+#Pipfile.lock
+
+# PEP 582; used by e.g. github.com/David-OConnor/pyflow
+__pypackages__/
+
+# Celery stuff
+celerybeat-schedule
+celerybeat.pid
+
+# SageMath parsed files
+*.sage.py
+
+# Environments
+.env
+.venv
+env/
+venv/
+ENV/
+env.bak/
+venv.bak/
+
+# Spyder project settings
+.spyderproject
+.spyproject
+
+# Rope project settings
+.ropeproject
+
+# mkdocs documentation
+/site
+
+# mypy
+.mypy_cache/
+.dmypy.json
+dmypy.json
+
+# Pyre type checker
+.pyre/
+
+# model weights
+yolov5*.pt
+
+# Gradio
+flagged/
+
+# git
+.git/

.gitattributes

@@ -0,0 +1,35 @@
+*.7z filter=lfs diff=lfs merge=lfs -text
+*.arrow filter=lfs diff=lfs merge=lfs -text
+*.bin filter=lfs diff=lfs merge=lfs -text
+*.bz2 filter=lfs diff=lfs merge=lfs -text
+*.ckpt filter=lfs diff=lfs merge=lfs -text
+*.ftz filter=lfs diff=lfs merge=lfs -text
+*.gz filter=lfs diff=lfs merge=lfs -text
+*.h5 filter=lfs diff=lfs merge=lfs -text
+*.joblib filter=lfs diff=lfs merge=lfs -text
+*.lfs.* filter=lfs diff=lfs merge=lfs -text
+*.mlmodel filter=lfs diff=lfs merge=lfs -text
+*.model filter=lfs diff=lfs merge=lfs -text
+*.msgpack filter=lfs diff=lfs merge=lfs -text
+*.npy filter=lfs diff=lfs merge=lfs -text
+*.npz filter=lfs diff=lfs merge=lfs -text
+*.onnx filter=lfs diff=lfs merge=lfs -text
+*.ot filter=lfs diff=lfs merge=lfs -text
+*.parquet filter=lfs diff=lfs merge=lfs -text
+*.pb filter=lfs diff=lfs merge=lfs -text
+*.pickle filter=lfs diff=lfs merge=lfs -text
+*.pkl filter=lfs diff=lfs merge=lfs -text
+*.pt filter=lfs diff=lfs merge=lfs -text
+*.pth filter=lfs diff=lfs merge=lfs -text
+*.rar filter=lfs diff=lfs merge=lfs -text
+*.safetensors filter=lfs diff=lfs merge=lfs -text
+saved_model/**/* filter=lfs diff=lfs merge=lfs -text
+*.tar.* filter=lfs diff=lfs merge=lfs -text
+*.tflite filter=lfs diff=lfs merge=lfs -text
+*.tgz filter=lfs diff=lfs merge=lfs -text
+*.wasm filter=lfs diff=lfs merge=lfs -text
+*.xz filter=lfs diff=lfs merge=lfs -text
+*.zip filter=lfs diff=lfs merge=lfs -text
+*.zst filter=lfs diff=lfs merge=lfs -text
+*tfevents* filter=lfs diff=lfs merge=lfs -text
+examples/Singapore_Skyline_2019-10.jpg filter=lfs diff=lfs merge=lfs -text

.gitignore

@@ -127,3 +127,9 @@ dmypy.json
 
 # Pyre type checker
 .pyre/
+
+# model weights
+yolov5*.pt
+
+# Gradio
+flagged/

Dockerfile

@@ -0,0 +1,22 @@
+FROM python:3.10.8-slim
+
+ARG DEBIAN_FRONTEND=noninteractive
+
+WORKDIR /app
+COPY . /app
+
+RUN apt-get update && apt-get install -y \
+    ffmpeg libsm6 libxext6
+RUN apt-get clean && rm -rf /tmp/* /var/tmp/*
+
+RUN python -m pip install --upgrade pip
+RUN python -m pip install -r requirements.txt
+
+ENV LC_ALL C.UTF-8 
+ENV LANG C.UTF-8
+
+# container listens to port 7860
+EXPOSE 7860
+
+# Start Gradio application
+CMD ["python", "app.py", "--host", "0.0.0.0", "--port", "7860"]

LICENSE

@@ -1,201 +1,674 @@
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+<https://www.gnu.org/licenses/why-not-lgpl.html>.

README.md

@@ -1 +1,48 @@
-# gradio-ml-skeleton
+# Gradio Model Server Skeleton
+
+This repository contains a Gradio skeleton application which can be used to rapid prototype a demonstration app for your next machine learning/deep learning model.
+
+To experiment and get a feeling on how to use this skeleton, a sample YOLOv5 object detection model is included in this proejct. Follow the installation and setup instructions to run the deep learning application.
+
+## Pre-requisite & Setup
+
+Ensure to have a Python environment before setting up, preferably Python 3.8+.
+
+```sh
+apt-get update
+apt-get install ffmpeg libsm6 libxext6  -y
+```
+
+```sh
+pip install -r requirements.txt
+```
+
+```sh
+# for dev env, hot-reloading is enabled
+gradio app.py
+
+# for testing/UAT/prod env, ensure port number is cleared
+python app.py --host 0.0.0.0 --port 7860
+```
+
+## Docker alternative
+
+Alternatively, you can use docker to containerize the Gradio application.
+
+```sh
+# REQUIRED
+export docker_repo_name=gradio-ml-skeleton
+export docker_tag=dev_latest
+
+# build an image from Dockerfile
+sh build_docker.sh
+```
+
+```sh
+# creates a container layer over the image
+sh launch_docker.sh
+```
+
+## Application Preview
+
+<img src="assets/Web%20capture_2-12-2022_17491_tyh71-miniature-memory.jpeg" alt="Preview">

app.py

@@ -0,0 +1,21 @@
+'''
+main script for gradio application
+'''
+import argparse
+import gradio as gr
+from src.core.logger import logger
+from src.interface.yolov5 import yolov5_demo
+
+demo = gr.TabbedInterface(
+    [yolov5_demo],
+    ["YOLOv5 Demo"]
+)
+
+if __name__ == "__main__":
+    parser = argparse.ArgumentParser()
+    parser.add_argument("--host", default="0.0.0.0", type=str)
+    parser.add_argument(
+        "--port", help="will start gradio app on this port (if available)", default=7860, type=int)
+    args_all = parser.parse_args()
+    logger.info("Gradio Application live and running !")
+    demo.queue().launch(share=False, server_name=args_all.host, server_port=args_all.port)

build_docker.sh

@@ -0,0 +1,8 @@
+if [ ! -n "$docker_repo_name" ] || [ ! -n "$docker_tag" ]; then
+  echo "Error: Parameters not defined."
+  exit 1
+fi
+
+echo "docker_repo_name=$docker_repo_name"
+echo "docker_tag=$docker_tag"
+docker build -f Dockerfile -t $docker_repo_name:$docker_tag .

launch_docker.sh

@@ -0,0 +1,7 @@
+if [ ! -n "$docker_repo_name" ] || [ ! -n "$docker_tag" ]; then
+  echo "Error: Parameters not defined."
+  exit 1
+fi
+
+docker run -it -p 7860:7860 \
+  $docker_repo_name:$docker_tag

requirements.txt

@@ -0,0 +1,141 @@
+aiohttp==3.8.3
+aiosignal==1.3.1
+anyio==3.6.2
+argon2-cffi==21.3.0
+argon2-cffi-bindings==21.2.0
+asttokens==2.2.0
+async-timeout==4.0.2
+attrs==22.1.0
+Babel==2.11.0
+backcall==0.2.0
+bcrypt==4.0.1
+beautifulsoup4==4.11.1
+bleach==5.0.1
+certifi==2022.9.24
+cffi==1.15.1
+charset-normalizer==2.1.1
+click==8.1.3
+colorama==0.4.6
+contourpy==1.0.6
+cryptography==38.0.4
+cycler==0.11.0
+debugpy==1.6.4
+decorator==5.1.1
+defusedxml==0.7.1
+entrypoints==0.4
+executing==1.2.0
+fastapi==0.88.0
+fastjsonschema==2.16.2
+ffmpy==0.3.0
+fonttools==4.38.0
+frozenlist==1.3.3
+fsspec==2022.11.0
+gitdb==4.0.10
+GitPython==3.1.29
+gradio==3.12.0
+h11==0.12.0
+httpcore==0.15.0
+httpx==0.23.1
+idna==3.4
+ipykernel==6.17.1
+ipython==8.7.0
+ipython-genutils==0.2.0
+jedi==0.18.2
+Jinja2==3.1.2
+joblib==1.2.0
+json5==0.9.10
+jsonschema==4.17.1
+jupyter-server==1.23.3
+jupyter-server-mathjax==0.2.6
+jupyter_client==7.4.7
+jupyter_core==5.1.0
+jupyterlab==3.5.0
+jupyterlab-git==0.40.1
+jupyterlab-pygments==0.2.2
+jupyterlab_server==2.16.3
+kiwisolver==1.4.4
+linkify-it-py==1.0.3
+markdown-it-py==2.1.0
+MarkupSafe==2.1.1
+matplotlib==3.6.2
+matplotlib-inline==0.1.6
+mdit-py-plugins==0.3.1
+mdurl==0.1.2
+mistune==2.0.4
+multidict==6.0.2
+nbclassic==0.4.8
+nbclient==0.7.2
+nbconvert==7.2.5
+nbdime==3.1.1
+nbformat==5.7.0
+nest-asyncio==1.5.6
+notebook==6.5.2
+notebook_shim==0.2.2
+numpy==1.23.5
+nvidia-cublas-cu11==11.10.3.66
+nvidia-cuda-nvrtc-cu11==11.7.99
+nvidia-cuda-runtime-cu11==11.7.99
+nvidia-cudnn-cu11==8.5.0.96
+opencv-python==4.6.0.66
+orjson==3.8.2
+packaging==21.3
+pandas==1.5.2
+pandocfilters==1.5.0
+paramiko==2.12.0
+parso==0.8.3
+pexpect==4.8.0
+pickleshare==0.7.5
+Pillow==9.3.0
+platformdirs==2.5.4
+plotly==5.11.0
+prometheus-client==0.15.0
+prompt-toolkit==3.0.33
+psutil==5.9.4
+ptyprocess==0.7.0
+pure-eval==0.2.2
+pycparser==2.21
+pycryptodome==3.16.0
+pydantic==1.10.2
+pydub==0.25.1
+Pygments==2.13.0
+PyNaCl==1.5.0
+pyparsing==3.0.9
+pyrsistent==0.19.2
+python-dateutil==2.8.2
+python-multipart==0.0.5
+pytz==2022.6
+PyYAML==6.0
+pyzmq==24.0.1
+requests==2.28.1
+rfc3986==1.5.0
+scikit-learn==1.1.3
+scipy==1.9.3
+seaborn==0.12.1
+Send2Trash==1.8.0
+six==1.16.0
+smmap==5.0.0
+sniffio==1.3.0
+soupsieve==2.3.2.post1
+stack-data==0.6.2
+starlette==0.22.0
+tenacity==8.1.0
+terminado==0.17.0
+threadpoolctl==3.1.0
+tinycss2==1.2.1
+tomli==2.0.1
+-f https://download.pytorch.org/whl/torch_stable.html 
+torch==1.13.0
+-f https://download.pytorch.org/whl/torch_stable.html 
+torchvision==0.14.0+cpu
+tornado==6.2
+tqdm==4.64.1
+traitlets==5.6.0
+typing_extensions==4.4.0
+uc-micro-py==1.0.1
+urllib3==1.26.13
+uvicorn==0.20.0
+wcwidth==0.2.5
+webencodings==0.5.1
+websocket-client==1.4.2
+websockets==10.4
+yarl==1.8.1

src/core/logger.py

@@ -0,0 +1,8 @@
+'''
+Setting up a logger.
+'''
+import logging
+
+logger = logging.getLogger(__name__)
+logger.setLevel(logging.DEBUG)
+logger.addHandler(logging.StreamHandler())

src/core/utils.py

@@ -0,0 +1,14 @@
+'''
+Python utility module
+'''
+from datetime import datetime
+import pytz
+
+def current_sg_time() -> datetime:
+    """
+    It returns the current time in Singapore
+    :return: A datetime object with the current time in Singapore.
+    """
+    time_zone = pytz.timezone("Asia/Singapore")
+    my_time = datetime.utcnow()
+    return my_time.astimezone(time_zone)

src/interface/yolov5.py

@@ -0,0 +1,77 @@
+'''
+YOLOv5 Interface Module
+'''
+# packages
+from typing import Tuple, Optional
+import glob
+import numpy as np
+import torch
+import gradio as gr
+import pandas as pd
+import PIL
+
+
+# modules
+from src.core.logger import logger
+from src.core.utils import current_sg_time
+from src.model.yolov5 import model
+
+
+def yolov5_demo_fn(
+    image: np.array,
+    nms_threshold: Optional[float] = 0.25,
+    conf_threshold: Optional[float] = 0.3
+) -> Tuple[PIL.Image.Image, pd.DataFrame]:
+    """
+    It takes an image as input, runs it through a model, and returns the rendered image
+    and the bounding box coordinates
+
+    :param image: np.array
+    :type image: np.array
+    :return: The first return value is a PIL image, the second is a pandas dataframe.
+    """
+    try:
+        logger.info("\nYOLOv5 demo function invoked\ndate/time: %s",
+                    current_sg_time())
+
+        # model config
+        model.conf = conf_threshold
+        model.iou = nms_threshold
+
+        # disables automatic differential gradients during inference
+        with torch.inference_mode(True):
+            results = model(image)
+        return results.render()[0], results.pandas().xyxy[0].round(decimals=2)
+    except Exception as e:
+        logger.error("Error Caught: %s", e)
+    finally:
+        logger.info("YOLOv5 demo function complete")
+
+DESCRIPTION = """
+You can use YOLOv5 to run object detection on common objects of interests (based on COCO classes). To use it, simply uplaod an image and click submit.
+You can also use the confidence threshold slider to set a threshold to filter out low probability predictions 
+and Non-Maximum Suppression (NMS) to set a threshold to filter out duplicate predictions.
+"""
+
+ARTICLE = """
+#### License
+YOLOv5 is open-sourced by Ultralytics for open source and academic proejcts under a **GPL 3.0 License**.
+"""
+
+yolov5_demo = gr.Interface(
+    fn=yolov5_demo_fn,
+    inputs=[
+        gr.Image(type="pil", label="Input Image"),
+        gr.Slider(0, 1, value=0.25,
+                  label="Non-Maximum Suppression (NMS) Threshold"),
+        gr.Slider(0, 1, value=0.3, label="Confidence Threshold")
+    ],
+    outputs=[gr.Image(type="numpy", label="Render"),
+             gr.Dataframe(label="BBox (COCO), Confidence, Class")],
+    title="YOLOv5 Object Detection",
+    description=DESCRIPTION,
+    article=ARTICLE,
+    examples=list(map(lambda x: [x, 0.25, 0.3], glob.glob("examples/*"))),
+    allow_flagging="never"
+)
+logger.info("YOLOv5 Interface Built")

src/model/yolov5.py

@@ -0,0 +1,19 @@
+'''
+module to load yolov5* model from the ultralytics/yolov5 repo
+'''
+import torch
+
+
+def load_model():
+    """
+    It loads the YOLOv5s model from the PyTorch Hub
+    :return: A model
+    """
+    device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+    _model = torch.hub.load("ultralytics/yolov5", "yolov5m6", device=device)
+    _model_agnostic = True  # NMS class-agnostic
+    _model.amp = True  # enable Automatic Mixed Precision (NMS) for inference
+    return _model
+
+
+model = load_model()