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" |
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########### | |
# BUILDER # | |
########### | |
FROM python:3.10.8-slim AS builder | |
# Upgrade pip | |
RUN pip install --upgrade pip | |
# Install a specific poetry version, it can be useful to avoid breaking changes | |
RUN pip install poetry==1.8.3 |
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name: Create release | |
on: | |
push: | |
tags: | |
- v* | |
permissions: | |
contents: write |
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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" |
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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" |
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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 |
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: |
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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__) |
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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 |