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https://github.com/lnxusr1/kenzy_image
Computer Vision module for Python 3.x+ to perform face/object/motion detection and recognition.
https://github.com/lnxusr1/kenzy_image
Last synced: 25 days ago
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Computer Vision module for Python 3.x+ to perform face/object/motion detection and recognition.
- Host: GitHub
- URL: https://github.com/lnxusr1/kenzy_image
- Owner: lnxusr1
- License: mit
- Created: 2022-12-29T19:55:40.000Z (about 2 years ago)
- Default Branch: main
- Last Pushed: 2023-06-25T20:27:44.000Z (over 1 year ago)
- Last Synced: 2024-10-12T00:38:45.321Z (3 months ago)
- Language: Python
- Size: 22.4 MB
- Stars: 1
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- Changelog: CHANGELOG.md
- License: LICENSE
Awesome Lists containing this project
README
# kenzy_image · [](https://github.com/lnxusr1/kenzy_image/blob/master/LICENSE)   
This module is dedicated to simplifying the interactions required for face detection, face recognition, object detection, and motion detection. Visit our main site: [https://kenzy.ai/](https://kenzy.ai/)
More info available in the [documentation](https://image-docs.kenzy.ai/)
## Installation
The easiest way to install kenzy_image is with the following:
```
pip install kenzy-image
```
Just make sure you're running Python 3.6 or newer.
## Embedding into your program
Visit the [detector](https://image-docs.kenzy.ai/en/latest/detector/) page in the [documentation](https://image-docs.kenzy.ai/) for more information.
```
import cv2 # For webcam input
from kenzy_image import detector
# Create our Kenzy Detector Object
myImageDetector = detector(detectFaces=True,
detectObjects=True,
objModelType="ssd", # or yolo
detectMotion=True,
imageMarkupFaces=True,
scaleFactor=0.5)
# Add Named Faces to Recognize
myImageDetector.addFace("IMG_4291_portrait_jon.jpg", "Jon Doe")
myImageDetector.addFace("IMG_7033_portrait_jane.jpg", "Jane Doe")
# Open the camera stream
cam = cv2.VideoCapture(0)
while True:
# Read frame from camera
ret, frame = cam.read()
# Analyze with kenzy_image
myImageDetector.analyze(frame)
print("=======================")
print("FACES =", len(myImageDetector.faces))
print("OBJECTS =", [x.get("name") for x in myImageDetector.objects])
print("MOVEMENTS =", True if len(myImageDetector.movements) > 0 else False)
# Show the frame with markup
cv2.imshow('KENZY_IMAGE', myImageDetector.image)
# Loop until [Esc] or "q"
if cv2.waitKey(1) & 0xFF == ord('q'):
break
cam.release()
cv2.destroyAllWindows()
```
## Running as module
Options are as follows for starting kenzy_image:
```
python -m kenzy_image [OPTIONS]
```
For example, to switch the model to MobileNet v3's SSD model use:
```
python -m kenzy_image --object-detect-type ssd
```
Use ```--help``` for more information on options.
## References and Other Useful Links
Many thanks to those that build the models and core libraries that KENZY_IMAGE incorporates. Please find links to those below:
#### Face Detection & Recognition
- [Face Recognition Concepts and Examples](https://git.ece.iastate.edu/se_329_cylicon_valley/face_recognition)
- [Face Recognition Library](https://github.com/ageitgey/face_recognition)
#### Object Detection
- [COCO Inference Model & Config](https://github.com/zafarRehan/object_detection_COCO)
- [COCO Labels](https://tech.amikelive.com/node-718/what-object-categories-labels-are-in-coco-dataset/) <-- Better label set for frozen inference model
- [YOLOv7 Model](https://github.com/wongkinyiu/yolov7) <-- Source for the included [Yolov7-tiny.pt](https://github.com/WongKinYiu/yolov7/releases)
- [YOLOv7 Python Library](https://github.com/akashAD98/yolov7-pip-1)
### Motion Detection
- [Motion Detection Example](https://towardsdatascience.com/image-analysis-for-beginners-creating-a-motion-detector-with-opencv-4ca6faba4b42)
-----
## Help & Support
Help and additional details is available at [https://kenzy.ai](https://kenzy.ai)
Read the docs: [https://image-docs.kenzy.ai/](https://image-docs.kenzy.ai/)