These are example files from the tutorial by @boneskull as seen on Get on The Good Foot with MicroPython on the ESP32, Part 2
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| # import config. | |
| # You can change the default config with `make cnf="config_special.env" build` | |
| cnf ?= config.env | |
| include $(cnf) | |
| export $(shell sed 's/=.*//' $(cnf)) | |
| # import deploy config | |
| # You can change the default deploy config with `make cnf="deploy_special.env" release` | |
| dpl ?= deploy.env | |
| include $(dpl) |
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| """ | |
| This notebook will demontrate a pre-trained model to recognition plate number in an image. | |
| Make sure to follow the [installation instructions](https://github.com/imamdigmi/plate-number-recognition#setup) before you start. | |
| """ | |
| import numpy as np | |
| import os | |
| import six.moves.urllib as urllib | |
| import sys | |
| import tarfile | |
| import tensorflow as tf |
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| from flask import Flask, Response | |
| app = Flask(__name__) | |
| @app.route("/wav") | |
| def streamwav(): | |
| def generate(): | |
| with open("signals/song.wav", "rb") as fwav: | |
| data = fwav.read(1024) |
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| # -*- coding: utf-8 -*- | |
| import sys | |
| import numpy | |
| numpy.seterr(all='ignore') | |
| ''' |