diff --git a/YOLOv5-Streamlit-Deployment/.gitignore b/YOLOv5-Streamlit-Deployment/.gitignore deleted file mode 100644 index a5f95ae5d9b9fc43eb31cfe3458ae229acbf05f7..0000000000000000000000000000000000000000 --- a/YOLOv5-Streamlit-Deployment/.gitignore +++ /dev/null @@ -1,255 +0,0 @@ -# Repo-specific GitIgnore ---------------------------------------------------------------------------------------------- -*.jpg -*.jpeg -*.png -*.bmp -*.tif -*.tiff -*.heic -*.JPG -*.JPEG -*.PNG -*.BMP -*.TIF -*.TIFF -*.HEIC -*.mp4 -*.mov -*.MOV -*.avi -*.data -*.json -*.cfg -!setup.cfg -!cfg/yolov3*.cfg - -storage.googleapis.com -runs/* - - -!data/*.yaml -!data/hyps -!data/scripts - -!data/*.sh - -results*.csv - -# Datasets ------------------------------------------------------------------------------------------------------------- -coco/ -coco128/ -VOC/ - -# MATLAB GitIgnore ----------------------------------------------------------------------------------------------------- -*.m~ -*.mat -!targets*.mat - -# Neural Network weights ----------------------------------------------------------------------------------------------- -*.weights -*.pt -*.pb -*.onnx -*.engine -*.mlmodel -*.torchscript -*.tflite -*.h5 -*_saved_model/ -*_web_model/ -*_openvino_model/ -darknet53.conv.74 -yolov3-tiny.conv.15 - -# GitHub Python GitIgnore ---------------------------------------------------------------------------------------------- -# Byte-compiled / optimized / DLL files -__pycache__/ -*.py[cod] -*$py.class - -# C extensions -*.so - -# Distribution / packaging -.Python -env/ -build/ -develop-eggs/ -dist/ -downloads/ -eggs/ -.eggs/ -lib/ -lib64/ -parts/ -sdist/ -var/ -wheels/ -*.egg-info/ -/wandb/ -.installed.cfg -*.egg - - -# 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/ -.coverage -.coverage.* -.cache -nosetests.xml -coverage.xml -*.cover -.hypothesis/ - -# Translations -*.mo -*.pot - -# Django stuff: -*.log -local_settings.py - -# Flask stuff: -instance/ -.webassets-cache - -# Scrapy stuff: -.scrapy - -# Sphinx documentation -docs/_build/ - -# PyBuilder -target/ - -# Jupyter Notebook -.ipynb_checkpoints - -# pyenv -.python-version - -# celery beat schedule file -celerybeat-schedule - -# SageMath parsed files -*.sage.py - -# dotenv -.env - -# virtualenv -.venv* -venv*/ -ENV*/ - -# Spyder project settings -.spyderproject -.spyproject - -# Rope project settings -.ropeproject - -# mkdocs documentation -/site - -# mypy -.mypy_cache/ - - -# https://github.com/github/gitignore/blob/master/Global/macOS.gitignore ----------------------------------------------- - -# General -*/.DS_Store -.DS_Store -.AppleDouble -.LSOverride - -# Icon must end with two \r -Icon -Icon? - -# Thumbnails -._* - -# Files that might appear in the root of a volume -.DocumentRevisions-V100 -.fseventsd -.Spotlight-V100 -.TemporaryItems -.Trashes -.VolumeIcon.icns -.com.apple.timemachine.donotpresent - -# Directories potentially created on remote AFP share -.AppleDB -.AppleDesktop -Network Trash Folder -Temporary Items -.apdisk - - -# https://github.com/github/gitignore/blob/master/Global/JetBrains.gitignore -# Covers JetBrains IDEs: IntelliJ, RubyMine, PhpStorm, AppCode, PyCharm, CLion, Android Studio and WebStorm -# Reference: https://intellij-support.jetbrains.com/hc/en-us/articles/206544839 - -# User-specific stuff: -.idea/* -.idea/**/workspace.xml -.idea/**/tasks.xml -.idea/dictionaries -.html # Bokeh Plots -.pg # TensorFlow Frozen Graphs -.avi # videos - -# Sensitive or high-churn files: -.idea/**/dataSources/ -.idea/**/dataSources.ids -.idea/**/dataSources.local.xml -.idea/**/sqlDataSources.xml -.idea/**/dynamic.xml -.idea/**/uiDesigner.xml - -# Gradle: -.idea/**/gradle.xml -.idea/**/libraries - -# CMake -cmake-build-debug/ -cmake-build-release/ - -# Mongo Explorer plugin: -.idea/**/mongoSettings.xml - -## File-based project format: -*.iws - -## Plugin-specific files: - -# IntelliJ -out/ - -# mpeltonen/sbt-idea plugin -.idea_modules/ - -# JIRA plugin -atlassian-ide-plugin.xml - -# Cursive Clojure plugin -.idea/replstate.xml - -# Crashlytics plugin (for Android Studio and IntelliJ) -com_crashlytics_export_strings.xml -crashlytics.properties -crashlytics-build.properties -fabric.properties diff --git a/YOLOv5-Streamlit-Deployment/.pre-commit-config.yaml b/YOLOv5-Streamlit-Deployment/.pre-commit-config.yaml deleted file mode 100644 index 8505274918599e83376eb930a522b6472f29e1ee..0000000000000000000000000000000000000000 --- a/YOLOv5-Streamlit-Deployment/.pre-commit-config.yaml +++ /dev/null @@ -1,67 +0,0 @@ -# Define hooks for code formations -# Will be applied on any updated commit files if a user has installed and linked commit hook - -default_language_version: - python: python3.8 - -# Define bot property if installed via https://github.com/marketplace/pre-commit-ci -ci: - autofix_prs: true - autoupdate_commit_msg: '[pre-commit.ci] pre-commit suggestions' - autoupdate_schedule: monthly - # submodules: true - -repos: - - repo: https://github.com/pre-commit/pre-commit-hooks - rev: v4.2.0 - hooks: - - id: end-of-file-fixer - - id: trailing-whitespace - - id: check-case-conflict - - id: check-yaml - - id: check-toml - - id: pretty-format-json - - id: check-docstring-first - - - repo: https://github.com/asottile/pyupgrade - rev: v2.32.1 - hooks: - - id: pyupgrade - name: Upgrade code - args: [ --py37-plus ] - - - repo: https://github.com/PyCQA/isort - rev: 5.10.1 - hooks: - - id: isort - name: Sort imports - - - repo: https://github.com/pre-commit/mirrors-yapf - rev: v0.32.0 - hooks: - - id: yapf - name: YAPF formatting - - - repo: https://github.com/executablebooks/mdformat - rev: 0.7.14 - hooks: - - id: mdformat - name: MD formatting - additional_dependencies: - - mdformat-gfm - - mdformat-black - exclude: | - (?x)^( - README.md - )$ - - - repo: https://github.com/asottile/yesqa - rev: v1.3.0 - hooks: - - id: yesqa - - - repo: https://github.com/PyCQA/flake8 - rev: 4.0.1 - hooks: - - id: flake8 - name: PEP8 diff --git a/YOLOv5-Streamlit-Deployment/LICENSE b/YOLOv5-Streamlit-Deployment/LICENSE deleted file mode 100644 index 212d164a4871d3e81322b906040d24e3ac1f27e9..0000000000000000000000000000000000000000 --- a/YOLOv5-Streamlit-Deployment/LICENSE +++ /dev/null @@ -1,21 +0,0 @@ -MIT License - -Copyright (c) 2022 Thepbordin Jaiinsom - -Permission is hereby granted, free of charge, to any person obtaining a copy -of this software and associated documentation files (the "Software"), to deal -in the Software without restriction, including without limitation the rights -to use, copy, modify, merge, publish, distribute, sublicense, and/or sell -copies of the Software, and to permit persons to whom the Software is -furnished to do so, subject to the following conditions: - -The above copyright notice and this permission notice shall be included in all -copies or substantial portions of the Software. - -THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR -IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, -FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE -AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER -LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, -OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE -SOFTWARE. diff --git a/YOLOv5-Streamlit-Deployment/README.md b/YOLOv5-Streamlit-Deployment/README.md deleted file mode 100644 index 34e314498c3821cd1ce66939a0eb1e7a4d52ddf2..0000000000000000000000000000000000000000 --- a/YOLOv5-Streamlit-Deployment/README.md +++ /dev/null @@ -1,74 +0,0 @@ - -# 🚀 YOLOv5 Streamlit Deployment -[![HitCount](https://hits.dwyl.com/thepbordin/YOLOv5-Streamlit-Deployment.svg?style=flat&show=unique)](http://hits.dwyl.com/thepbordin/YOLOv5-Streamlit-Deployment) - - -A Easy way to deploy [YOLOv5](https://github.com/ultralytics/yolov5) object detection model with [Streamlit](https://streamlit.io/). - -**Please feel free to use/edit.** - - -code modified by GitHub/thepbordin from GitHub/zhoroh - -## ✨ Features - -- YOLO Weights Source - - Load from Local - - Download Weights from URL -- Example Dataset - - Videos - - Images - - Upload Data - - Video - - Image -- Select computing device (cuda/cpu) - - - -## ⚙️ Installation - - - -### Local Use -1. Install Requirements - `pip install -r requirements.txt` -2. Install ffmpeg (for video inferencing) - - For Windows [read here](https://www.geeksforgeeks.org/how-to-install-ffmpeg-on-windows/) - - For Mac (brew) - `brew install ffmpeg` -3. Strart Stremlit - ``` - cd YOLOv5-Streamlit-Deployment - streamlit run app.py - ``` -### Streamlit Cloud -1. Edit a configuration in app.py (read ⚙️ Config Instruction) -2. (Optional) Upload example datas in - - `example_images` - - `example_videos` -4. Deploy on [Streamlit](https://share.streamlit.io/deploy) - - -## ⚙️ Config Instruction -### Download model from URL - -1. Upload model to [Internet Archive](https://archive.org/) -2. Go to your uploaded file page. -3. From `DOWNLOAD OPTIONS` select `SHOW ALL` -4. Right click at .pt and Copy link address. -5. Edit config in [app.py](https://github.com/thepbordin/YOLOv5-Streamlit-Deployment/blob/main/app.py) - - ```python - cfg_enable_url_download = True - url = "your_model_url" - ``` - -### Use local .pt file: -Edit config in [app.py](https://github.com/thepbordin/YOLOv5-Streamlit-Deployment/blob/main/app.py) -```python -## CFG -cfg_model_path = "models/your_model_name.pt" -``` - -## Reference -[Yolov5 Real-time Inference using Streamlit](https://github.com/moaaztaha/Yolo-Interface-using-Streamlit) diff --git a/YOLOv5-Streamlit-Deployment/app.py b/YOLOv5-Streamlit-Deployment/app.py deleted file mode 100644 index 64b778a724a56cfdae317134e04f388e9a415739..0000000000000000000000000000000000000000 --- a/YOLOv5-Streamlit-Deployment/app.py +++ /dev/null @@ -1,182 +0,0 @@ -import streamlit as st -import torch -from PIL import Image -from io import * -import glob -from datetime import datetime -import os -import wget -from video_predict import runVideo - - -# Configurations -CFG_MODEL_PATH = "models/yourModel.pt" -CFG_ENABLE_URL_DOWNLOAD = True -CFG_ENABLE_VIDEO_PREDICTION = True -if CFG_ENABLE_URL_DOWNLOAD: - # Configure this if you set cfg_enable_url_download to True - url = "https://archive.org/download/yoloTrained/yoloTrained.pt" -# End of Configurations - - -def imageInput(model, src): - - if src == 'Upload your own data.': - image_file = st.file_uploader( - "Upload An Image", type=['png', 'jpeg', 'jpg']) - col1, col2 = st.columns(2) - if image_file is not None: - img = Image.open(image_file) - with col1: - st.image(img, caption='Uploaded Image', - use_column_width='always') - ts = datetime.timestamp(datetime.now()) - imgpath = os.path.join('data/uploads', str(ts)+image_file.name) - outputpath = os.path.join( - 'data/outputs', os.path.basename(imgpath)) - with open(imgpath, mode="wb") as f: - f.write(image_file.getbuffer()) - - with st.spinner(text="Predicting..."): - # Load model - pred = model(imgpath) - pred.render() - # save output to file - for im in pred.ims: - im_base64 = Image.fromarray(im) - im_base64.save(outputpath) - - # Predictions - img_ = Image.open(outputpath) - with col2: - st.image(img_, caption='Model Prediction(s)', - use_column_width='always') - - elif src == 'From example data.': - # Image selector slider - imgpaths = glob.glob('data/example_images/*') - if len(imgpaths) == 0: - st.write(".") - st.error( - 'No images found, Please upload example images in data/example_images', icon="") - return - imgsel = st.slider('Select random images from example data.', - min_value=1, max_value=len(imgpaths), step=1) - image_file = imgpaths[imgsel-1] - submit = st.button("Predict!") - col1, col2 = st.columns(2) - with col1: - img = Image.open(image_file) - st.image(img, caption='Selected Image', use_column_width='always') - with col2: - if image_file is not None and submit: - with st.spinner(text="Predicting..."): - # Load model - - pred = model(image_file) - pred.render() - # save output to file - for im in pred.ims: - im_base64 = Image.fromarray(im) - im_base64.save(os.path.join( - 'data/outputs', os.path.basename(image_file))) - # Display predicton - img_ = Image.open(os.path.join( - 'data/outputs', os.path.basename(image_file))) - st.image(img_, caption='Model Prediction(s)') - - -def videoInput(model, src): - if src == 'Upload your own data.': - uploaded_video = st.file_uploader( - "Upload A Video", type=['mp4', 'mpeg', 'mov']) - pred_view = st.empty() - warning = st.empty() - if uploaded_video != None: - - # Save video to disk - ts = datetime.timestamp(datetime.now()) # timestamp a upload - uploaded_video_path = os.path.join( - 'data/uploads', str(ts)+uploaded_video.name) - with open(uploaded_video_path, mode='wb') as f: - f.write(uploaded_video.read()) - - # Display uploaded video - with open(uploaded_video_path, 'rb') as f: - video_bytes = f.read() - st.video(video_bytes) - st.write("Uploaded Video") - submit = st.button("Run Prediction") - if submit: - runVideo(model, uploaded_video_path, pred_view, warning) - - elif src == 'From example data.': - # Image selector slider - videopaths = glob.glob('data/example_videos/*') - if len(videopaths) == 0: - st.error( - 'No videos found, Please upload example videos in data/example_videos', icon="⚠️") - return - imgsel = st.slider('Select random video from example data.', - min_value=1, max_value=len(videopaths), step=1) - pred_view = st.empty() - video = videopaths[imgsel-1] - submit = st.button("Predict!") - if submit: - runVideo(model, video, pred_view, warning) - - -def main(): - if CFG_ENABLE_URL_DOWNLOAD: - downloadModel() - - else: - if not os.path.exists(CFG_MODEL_PATH): - st.error( - 'Model not found, please config if you wish to download model from url set `cfg_enable_url_download = True` ', icon="⚠️") - - # -- Sidebar - st.sidebar.title('⚙️ Options') - datasrc = st.sidebar.radio("Select input source.", [ - 'From example data.', 'Upload your own data.']) - - if CFG_ENABLE_VIDEO_PREDICTION: - option = st.sidebar.radio("Select input type.", ['Image', 'Video']) - else: - option = st.sidebar.radio("Select input type.", ['Image']) - if torch.cuda.is_available(): - deviceoption = st.sidebar.radio("Select compute Device.", [ - 'cpu', 'cuda'], disabled=False, index=1) - else: - deviceoption = st.sidebar.radio("Select compute Device.", [ - 'cpu', 'cuda'], disabled=True, index=0) - # -- End of Sidebar - - st.header('📦 YOLOv5 Streamlit Deployment Example') - st.sidebar.markdown( - "https://github.com/thepbordin/Obstacle-Detection-for-Blind-people-Deployment") - - if option == "Image": - imageInput(loadmodel(deviceoption), datasrc) - elif option == "Video": - videoInput(loadmodel(deviceoption), datasrc) - - -# Downlaod Model from url. -@st.cache_resource -def downloadModel(): - if not os.path.exists(CFG_MODEL_PATH): - wget.download(url, out="models/") - - -@st.cache_resource -def loadmodel(device): - if CFG_ENABLE_URL_DOWNLOAD: - CFG_MODEL_PATH = f"models/{url.split('/')[-1:][0]}" - model = torch.hub.load('ultralytics/yolov5', 'custom', - path=CFG_MODEL_PATH, force_reload=True, device=device) - return model - - -if __name__ == '__main__': - main() diff --git a/YOLOv5-Streamlit-Deployment/data/.DS_Store b/YOLOv5-Streamlit-Deployment/data/.DS_Store deleted file mode 100644 index 9ea2d7a140d3fb7ee4a918a6258784357eadea0a..0000000000000000000000000000000000000000 Binary files a/YOLOv5-Streamlit-Deployment/data/.DS_Store and /dev/null differ diff --git a/YOLOv5-Streamlit-Deployment/data/example_images/.DS_Store b/YOLOv5-Streamlit-Deployment/data/example_images/.DS_Store deleted file mode 100644 index 2f4e94a0a1f488eb1a30c360aecd0310fa030821..0000000000000000000000000000000000000000 Binary files a/YOLOv5-Streamlit-Deployment/data/example_images/.DS_Store and /dev/null differ diff --git a/YOLOv5-Streamlit-Deployment/data/example_images/.gitignore b/YOLOv5-Streamlit-Deployment/data/example_images/.gitignore deleted file mode 100644 index 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a/YOLOv5-Streamlit-Deployment/data/outputs/.gitignore +++ /dev/null @@ -1,4 +0,0 @@ -# Ignore everything in this directory -* -# Except this file -!.gitignore \ No newline at end of file diff --git a/YOLOv5-Streamlit-Deployment/data/uploads/.DS_Store b/YOLOv5-Streamlit-Deployment/data/uploads/.DS_Store deleted file mode 100644 index 8687ff5a254a6a254c9a428b6f85328b50d46048..0000000000000000000000000000000000000000 Binary files a/YOLOv5-Streamlit-Deployment/data/uploads/.DS_Store and /dev/null differ diff --git a/YOLOv5-Streamlit-Deployment/data/uploads/.gitignore b/YOLOv5-Streamlit-Deployment/data/uploads/.gitignore deleted file mode 100644 index 86d0cb2726c6c7c179b99520c452dd1b68e7a813..0000000000000000000000000000000000000000 --- a/YOLOv5-Streamlit-Deployment/data/uploads/.gitignore +++ /dev/null @@ -1,4 +0,0 @@ -# Ignore everything in this directory -* -# Except this file -!.gitignore \ No newline at end of file diff --git a/YOLOv5-Streamlit-Deployment/data/video_frames/.DS_Store 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b/YOLOv5-Streamlit-Deployment/packages.txt deleted file mode 100644 index c5b9bc1f242a14c5fbab758590839acbc8bc6d10..0000000000000000000000000000000000000000 --- a/YOLOv5-Streamlit-Deployment/packages.txt +++ /dev/null @@ -1,2 +0,0 @@ -libgl1 -ffmpeg \ No newline at end of file diff --git a/YOLOv5-Streamlit-Deployment/requirements.txt b/YOLOv5-Streamlit-Deployment/requirements.txt deleted file mode 100644 index da246a1127d683d8280607508240eb54491d2f26..0000000000000000000000000000000000000000 --- a/YOLOv5-Streamlit-Deployment/requirements.txt +++ /dev/null @@ -1,32 +0,0 @@ -# YOLOv5 requirements -# Usage: pip install -r requirements.txt - -# Base ---------------------------------------- -matplotlib>=3.2.2 -numpy>=1.18.5 -opencv-python -Pillow>=7.1.2 -PyYAML>=5.3.1 -requests>=2.23.0 -scipy>=1.4.1 # Google Colab version -torch>=1.7.0 -torchvision>=0.8.1 -tqdm>=4.41.0 -protobuf<4.21.5 # https://github.com/ultralytics/yolov5/issues/8012 -ultralytics -# Logging ------------------------------------- -tensorboard>=2.4.1 -# wandb - -# Plotting ------------------------------------ -pandas>=1.1.4 -seaborn>=0.11.0 - - -# Extras -------------------------------------- -ipython # interactive notebook -psutil # system utilization -thop # FLOPs computation -streamlit -wget -ffmpeg-python diff --git a/YOLOv5-Streamlit-Deployment/video_predict.py b/YOLOv5-Streamlit-Deployment/video_predict.py deleted file mode 100644 index 97e7a79f99578a8bb6ceb7d9de94c651319029fa..0000000000000000000000000000000000000000 --- a/YOLOv5-Streamlit-Deployment/video_predict.py +++ /dev/null @@ -1,45 +0,0 @@ -import os -import os.path as osp -import cv2 -from PIL import Image -import streamlit as st - - -def runVideo(model, video, vdo_view, warn): - video_name = osp.basename(video) - outputpath = osp.join('data/video_output', video_name) - - # Create A Dir to save Video Frames - os.makedirs('data/video_frames', exist_ok=True) - frames_dir = osp.join('data/video_frames', video_name) - os.makedirs(frames_dir, exist_ok=True) - cap = cv2.VideoCapture(video) - frame_count = 0 - with st.spinner(text="Predicting..."): - warn.warning( - 'This is realtime prediction, If you wish to download the final prediction result wait until the process done.', icon="⚠️") - while True: - frame_count += 1 - ret, frame = cap.read() - if ret == False: - break - frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB) - result = model(frame) - result.render() - image = Image.fromarray(result.ims[0]) - vdo_view.image(image, caption='Current Model Prediction(s)') - image.save(osp.join(frames_dir, f'{frame_count}.jpg')) - cap.release() - # convert frames in dir to a single video file - os.system( - f'ffmpeg -framerate 30 -i {frames_dir}/%d.jpg -c:v libx264 -pix_fmt yuv420p {outputpath}') - # Clean up Frames Dir - os.system(f'rm -rf {frames_dir}') - - # Display Video - output_video = open(outputpath, 'rb') - output_video_bytes = output_video.read() - st.video(output_video_bytes) - st.write("Model Prediction") - vdo_view.empty() - warn.empty()