mexicantexan

package main

import (
	"context"
	"fmt"
	"log"
	"os"
	"strings"

	"github.com/aws/aws-lambda-go/lambda"

mexicantexan

# Adapted from https://www.immersivelimit.com/tutorials/create-coco-annotations-from-scratch/#create-custom-coco-dataset
# Aimed at solving problem for: https://mmdetection.readthedocs.io/en/v2.25.0/tutorials/customize_dataset.html
# haven't tested script with multi-category, only tested with binary classification

import json
import numpy as np
from skimage import measure  # (pip install scikit-image)
from shapely.geometry import Polygon, MultiPolygon  # (pip install Shapely)
from PIL import Image  # (pip install Pillow)
import os

mexicantexan

"""
For TensorFlow v2 and Keras you can limit gpu memory usage a couple of different ways, just add one of the following early on in your scripts
"""
import tensorflow as tf

physical_devices = tf.config.experimental.list_physical_devices('GPU')
tf.config.experimental.set_memory_growth(physical_devices[0], True)

"""
or