Yolov5-restapi-insector | Yolov5-restapi-insector
kandi X-RAY | Yolov5-restapi-insector Summary
kandi X-RAY | Yolov5-restapi-insector Summary
Yolov5-restapi-insector is a Jupyter Notebook library. Yolov5-restapi-insector has no bugs, it has no vulnerabilities and it has low support. You can download it from GitHub.
Yolov5-restapi-insector
Yolov5-restapi-insector
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Support
Yolov5-restapi-insector has a low active ecosystem.
It has 0 star(s) with 0 fork(s). There are 2 watchers for this library.
It had no major release in the last 6 months.
Yolov5-restapi-insector has no issues reported. There are no pull requests.
It has a neutral sentiment in the developer community.
The latest version of Yolov5-restapi-insector is current.
Quality
Yolov5-restapi-insector has no bugs reported.
Security
Yolov5-restapi-insector has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
License
Yolov5-restapi-insector does not have a standard license declared.
Check the repository for any license declaration and review the terms closely.
Without a license, all rights are reserved, and you cannot use the library in your applications.
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Yolov5-restapi-insector releases are not available. You will need to build from source code and install.
Installation instructions, examples and code snippets are available.
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Currently covering the most popular Java, JavaScript and Python libraries. See a Sample of Yolov5-restapi-insector
Yolov5-restapi-insector Key Features
No Key Features are available at this moment for Yolov5-restapi-insector.
Yolov5-restapi-insector Examples and Code Snippets
No Code Snippets are available at this moment for Yolov5-restapi-insector.
Community Discussions
No Community Discussions are available at this moment for Yolov5-restapi-insector.Refer to stack overflow page for discussions.
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install Yolov5-restapi-insector
To use the YOLOv5 Insect Recognition API, follow the steps below:.
Install the necessary dependencies: Flask: pip install flask Torch: pip install torch Pillow: pip install pillow
Download the YOLOv5 model: Visit the YOLOv5 GitHub repository and download the best.pt model file. Save the best.pt model file in the same directory as the API code.
Set up the Flask application: Create a new Python file (e.g., app.py) and copy the API code into it.
Configure the API: Open the app.py file and modify the following variables as needed: app.config['UPLOAD_FOLDER']: Specify the folder where uploaded images will be stored. app.config['ALLOWED_EXTENSIONS']: Define the allowed file extensions for uploads. model_path: Set the path to the best.pt model file. model.conf: Adjust the confidence threshold for object detection (default is 0.5).
Start the API: Run the Flask application by executing the app.py file. The API will start running on the specified host and port (default is http://localhost:5000).
Install the necessary dependencies: Flask: pip install flask Torch: pip install torch Pillow: pip install pillow
Download the YOLOv5 model: Visit the YOLOv5 GitHub repository and download the best.pt model file. Save the best.pt model file in the same directory as the API code.
Set up the Flask application: Create a new Python file (e.g., app.py) and copy the API code into it.
Configure the API: Open the app.py file and modify the following variables as needed: app.config['UPLOAD_FOLDER']: Specify the folder where uploaded images will be stored. app.config['ALLOWED_EXTENSIONS']: Define the allowed file extensions for uploads. model_path: Set the path to the best.pt model file. model.conf: Adjust the confidence threshold for object detection (default is 0.5).
Start the API: Run the Flask application by executing the app.py file. The API will start running on the specified host and port (default is http://localhost:5000).
Support
For any new features, suggestions and bugs create an issue on GitHub.
If you have any questions check and ask questions on community page Stack Overflow .
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