Metadata-Version: 2.1
Name: daisykit
Version: 0.1.20211116
Summary: Deploy AI Systems Yourself (DAISY) Kit. DaisyKit Python is the wrapper of DaisyKit SDK, an AI framework focusing on the ease of deployment.
Home-page: https://docs.daisykit.org/
Author: DaisyKit Team
Author-email: daisykit.team@gmail.com
Maintainer: DaisyKit Team
Maintainer-email: daisykit.team@gmail.com
License: Apache License 2.0
Platform: UNKNOWN
Classifier: Programming Language :: C++
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.5
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: numpy
Requires-Dist: tqdm
Requires-Dist: requests
Requires-Dist: portalocker
Requires-Dist: opencv-python

# DaisyKit Python

<https://pypi.org/project/daisykit/>

Deploy AI Systems Yourself (DAISY) Kit. DaisyKit Python is the wrapper of DaisyKit SDK, an AI framework focusing on the ease of deployment. This package only supports Ubuntu Linux - Python 3 now. We will add support for other platforms and models in the future.

## Install and run example

Install dependencies. Below commands are for Ubuntu. You can try other installation methods based on your OS.

```
sudo apt install pybind11-dev # Pybind11 - For Python/C++ Wrapper
sudo apt install libopencv-dev # For OpenCV
sudo apt install libvulkan-dev # Optional - For GPU support
```

Install DaisyKit

```
pip3 install --upgrade pip # Ensure pip is updated
pip3 install daisykit
```

**Face Detection with mask recognition:**

```py
import cv2
import json
from daisykit.utils import get_asset_file
import daisykit

config = {
    "face_detection_model": {
        "model": get_asset_file("models/face_detection/yolo_fastest_with_mask/yolo-fastest-opt.param"),
        "weights": get_asset_file("models/face_detection/yolo_fastest_with_mask/yolo-fastest-opt.bin"),
        "input_width": 320,
        "input_height": 320,
        "score_threshold": 0.7,
        "iou_threshold": 0.5,
        "use_gpu": False
    },
    "with_landmark": True,
    "facial_landmark_model": {
        "model": get_asset_file("models/facial_landmark/pfld-sim.param"),
        "weights": get_asset_file("models/facial_landmark/pfld-sim.bin"),
        "input_width": 112,
        "input_height": 112,
        "use_gpu": False
    }
}

face_detector_flow = daisykit.FaceDetectorFlow(json.dumps(config))

# Open video stream from webcam
vid = cv2.VideoCapture(0)

while(True):

    # Capture the video frame
    ret, frame = vid.read()

    frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)

    faces = face_detector_flow.Process(frame)
    # for face in faces:
    #     print([face.x, face.y, face.w, face.h,
    #           face.confidence, face.wearing_mask_prob])
    face_detector_flow.DrawResult(frame, faces)

    frame = cv2.cvtColor(frame, cv2.COLOR_RGB2BGR)

    # Display the resulting frame
    cv2.imshow('frame', frame)

    # The 'q' button is set as the
    # quitting button you may use any
    # desired button of your choice
    if cv2.waitKey(1) & 0xFF == ord('q'):
        break

# After the loop release the cap object
vid.release()
# Destroy all the windows
cv2.destroyAllWindows()
```

**Background Matting:**

```py
import cv2
import json
from daisykit.utils import get_asset_file
from daisykit import BackgroundMattingFlow

config = {
    "background_matting_model": {
        "model": get_asset_file("models/background_matting/erd/erdnet.param"),
        "weights": get_asset_file("models/background_matting/erd/erdnet.bin")
    }
}

# Load background
default_bg_file = get_asset_file("images/background.jpg")
background = cv2.imread(default_bg_file)
background = cv2.cvtColor(background, cv2.COLOR_BGR2RGB)

background_matting_flow = BackgroundMattingFlow(json.dumps(config), background)

# Open video stream from webcam
vid = cv2.VideoCapture(0)

while(True):

    # Capture the video frame
    ret, frame = vid.read()

    frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)

    mask = background_matting_flow.Process(frame)
    background_matting_flow.DrawResult(frame, mask)

    frame = cv2.cvtColor(frame, cv2.COLOR_RGB2BGR)

    # Display the resulting frame
    cv2.imshow('frame', frame)

    # The 'q' button is set as the
    # quitting button you may use any
    # desired button of your choice
    if cv2.waitKey(1) & 0xFF == ord('q'):
        break

# After the loop release the cap object
vid.release()
# Destroy all the windows
cv2.destroyAllWindows()
```

**Human Pose Detection:**

```py
import cv2
import json
from daisykit.utils import get_asset_file
from daisykit import HumanPoseMoveNetFlow

config = {
  "person_detection_model": {
    "model": get_asset_file("models/human_detection/ssd_mobilenetv2.param"),
    "weights": get_asset_file("models/human_detection/ssd_mobilenetv2.bin")
  },
  "human_pose_model": {
    "model": get_asset_file("models/human_pose_detection/movenet/lightning.param"),
    "weights": get_asset_file("models/human_pose_detection/movenet/lightning.bin"),
    "input_width": 192,
    "input_height": 192
  }
}

human_pose_flow = HumanPoseMoveNetFlow(json.dumps(config))

# Open video stream from webcam
vid = cv2.VideoCapture(0)

while(True):

    # Capture the video frame
    ret, frame = vid.read()

    frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)

    poses = human_pose_flow.Process(frame)
    human_pose_flow.DrawResult(frame, poses)

    print(poses)

    frame = cv2.cvtColor(frame, cv2.COLOR_RGB2BGR)

    # Display the resulting frame
    cv2.imshow('frame', frame)

    # The 'q' button is set as the
    # quitting button you may use any
    # desired button of your choice
    if cv2.waitKey(1) & 0xFF == ord('q'):
        break

# After the loop release the cap object
vid.release()
# Destroy all the windows
cv2.destroyAllWindows()
```

**Barcode Detection:**

```py
import cv2
import json
from daisykit.utils import get_asset_file
from daisykit import BarcodeScannerFlow

config = {
  "try_harder": True,
  "try_rotate": True
}

barcode_scanner_flow = BarcodeScannerFlow(json.dumps(config))

# Open video stream from webcam
vid = cv2.VideoCapture(0)

while(True):

    # Capture the video frame
    ret, frame = vid.read()

    frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)

    result = barcode_scanner_flow.Process(frame, draw=True)

    frame = cv2.cvtColor(frame, cv2.COLOR_RGB2BGR)

    # Display the resulting frame
    cv2.imshow('frame', frame)

    # The 'q' button is set as the
    # quitting button you may use any
    # desired button of your choice
    if cv2.waitKey(1) & 0xFF == ord('q'):
        break

# After the loop release the cap object
vid.release()
# Destroy all the windows
cv2.destroyAllWindows()
```

## Build Python package

Build environment: Ubuntu.

```
sudo apt install ninja-build
python3 -m pip install --user --upgrade twine
```

Build package:

```
python3 setup.py sdist
```

or

```
bash scripts/build_python.sh
```

Upload to Pypi (for DaisyKit authors only)

```
twine upload dist/*
```

## TODO

- Multiplatform build.


