lanzani

name: Create release

on:
  push:
    tags:
      - v*

permissions:
  contents: write

lanzani

import cv2
import numpy as np
import mediapipe as mp
from mediapipe.tasks import python
from mediapipe.tasks.python import vision
from mediapipe.framework.formats import landmark_pb2

# Model available to download here: https://developers.google.com/mediapipe/solutions/vision/pose_landmarker#models
model_path = "pose_landmarker_full.task"

lanzani

version: "3"

services:

  postgres-test:
    image: postgres:15.1-alpine

    ports:
      - "5432:5432"  # If port 5432 is already in use on the host machine, you can change this with: "5435:5432"

lanzani

27 is ODD, so I make 3n+1: 82
82 is EVEN, so I take half: 41
41 is ODD, so I make 3n+1: 124
124 is EVEN, so I take half: 62
62 is EVEN, so I take half: 31
31 is ODD, so I make 3n+1: 94
94 is EVEN, so I take half: 47
47 is ODD, so I make 3n+1: 142
142 is EVEN, so I take half: 71
71 is ODD, so I make 3n+1: 214

lanzani

Point id	Point label
0	"nose"
1	"left_eye"
2	"right_eye"
3	"left_ear"
4	"right_ear"
5	"left_shoulder"
6	"right_shoulder"
7	"left_elbow"

lanzani

Emoji list from gitmoji

Emoji	Usage	Tag
🎨	Improve structure / format of the code.	:art:
⚡	Improve performance.	:zap:
🔥	Remove code or files.	:fire:
🐛	Fix a bug.	:bug:
🚑️	Critical hotfix.	:ambulance:
✨	Introduce new features.	:sparkles:

lanzani

def test_gpu_support():
    """Check CUDA compatibility with TensorFlow & DLIB.

    """
    import os
    import dlib
    import tensorflow as tf
    print("[INFO] TensorFlow: ", tf.__version__)
    print("[INFO] DLIB: ", dlib.__version__)

lanzani

import jetson.inference as inference
import jetson.utils as utils

import cv2
import time

# Load the net with jetson inference
net1 = inference.detectNet("ssd-mobilenet-v2", threshold=0.5)

# Define video sources