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This is free and unencumbered software released into the public domain. | |
Anyone is free to copy, modify, publish, use, compile, sell, or | |
distribute this software, either in source code form or as a compiled | |
binary, for any purpose, commercial or non-commercial, and by any | |
means. | |
In jurisdictions that recognize copyright laws, the author or authors | |
of this software dedicate any and all copyright interest in the | |
software to the public domain. We make this dedication for the benefit |
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import com.google.protobuf.gradle.protobuf | |
import com.google.protobuf.gradle.protoc | |
plugins { | |
java | |
idea | |
id("com.google.protobuf") version "0.8.7" | |
} | |
repositories { |
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""" | |
author: Timothy C. Arlen | |
date: 28 Feb 2018 | |
Calculate Mean Average Precision (mAP) for a set of bounding boxes corresponding to specific | |
image Ids. Usage: | |
> python calculate_mean_ap.py | |
Will display a plot of precision vs recall curves at 10 distinct IoU thresholds as well as output |
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// Updated example from http://rosettacode.org/wiki/Hello_world/Web_server#Rust | |
// to work with Rust 1.0 beta | |
use std::net::{TcpStream, TcpListener}; | |
use std::io::{Read, Write}; | |
use std::thread; | |
fn handle_read(mut stream: &TcpStream) { | |
let mut buf = [0u8 ;4096]; |