semvec/pypi-packages huggingface dataset:
palazzetti-sdk-asset-parser 1.0.10
IoT Device Capability Parser
Requires Python: >=3.6

# Palazzetti SDK - Asset Parser

## Library to detect capabilities of Palazzetti's product based on static and dynamic data

Requires Python 3.6 and uses semver.

```python
import palazzetti_sdk_asset_parser as psap

def main():

    asset_parser = psap.AssetParser(get_alls={"STATUS":0}, get_stdt={"FAN2TYPE":3})
    asset_capabilities = asset_parser.parsed_data

    if (asset_capabilities.flag_has_fan): print("Product has main fan")

    if (asset_capabilities.value_product_is_on): print("Product is ON!")
    else: print("Product is OFF!")

main()
```
plotbbox 0.1.3
A package to plot pretty bounding boxes for object detection task
Requires Python: >=3.6
Keywords: object-detection,bounding-box,bbox,box

# plotbbox
A package to plot pretty bounding boxes for object detection task

![](https://raw.githubusercontent.com/developer0hye/plotbbox/master/figures/figure_1_examples.png)


# Install
```python
pip install plotbbox
```

# Example Usage


```python
import cv2
from plotbbox import plotBBox

img = cv2.imread("your_img.png")

label_table = {0: "person", 1: "car"}
color_table = {0: [0, 255, 0], 1: [0, 0, 255]} # order: b, g, r

bboxes = your_detection_algorithm(img) # Shape: (N, 5), [:, 0]: class index, [:, 1:]: xmin, ymin, xmax, ymax

for bbox in bboxes:
  
  class_idx = bbox[0]
  xmin, ymin, xmax, ymax = bbox[1:]

  plotBBox(img, 
           xmin, ymin, xmax, ymax, color=color_table[class_idx], thickness=1, 
           label=label_table[class_idx]) # plot bounding box on img

cv2.imwrite("bboxes_plotted_your_img.png", img)
```
Read [docs/example.py](https://github.com/developer0hye/plotbbox/blob/main/docs/example.py) and run for more details!