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<?xml version="1.0" encoding="UTF-8"?>
<project xmlns="http://maven.apache.org/POM/4.0.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 https://maven.apache.org/xsd/maven-4.0.0.xsd">
    <modelVersion>4.0.0</modelVersion>
    <groupId>org.lara</groupId>
    <artifactId>laraproject</artifactId>
    <version>0.0.1-SNAPSHOT</version>
    <name>laraproject</name>
    <description>Lara Project</description>
    <packaging>jar</packaging>
    <properties>

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<?xml version="1.0" encoding="UTF-8"?>
<project xmlns="http://maven.apache.org/POM/4.0.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 https://maven.apache.org/xsd/maven-4.0.0.xsd">
    <modelVersion>4.0.0</modelVersion>
    <groupId>org.lara</groupId>
    <artifactId>laraproject</artifactId>
    <version>0.0.1-SNAPSHOT</version>
    <name>laraproject</name>
    <description>Lara Project</description>
    <packaging>jar</packaging>
    <properties>

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log4j:WARN No appenders could be found for logger (org.deeplearning4j.nn.modelimport.keras.layers.embeddings.KerasEmbedding).
log4j:WARN Please initialize the log4j system properly.
log4j:WARN See http://logging.apache.org/log4j/1.2/faq.html#noconfig for more info.
Exception in thread "main" java.lang.ClassCastException: class org.deeplearning4j.nn.conf.layers.recurrent.LastTimeStep cannot be cast to class org.deeplearning4j.nn.conf.layers.FeedForwardLayer (org.deeplearning4j.nn.conf.layers.recurrent.LastTimeStep and org.deeplearning4j.nn.conf.layers.FeedForwardLayer are in unnamed module of loader 'app')
	at org.deeplearning4j.nn.modelimport.keras.layers.recurrent.KerasLSTM.setWeights(KerasLSTM.java:449)
	at org.deeplearning4j.nn.modelimport.keras.utils.KerasModelUtils.importWeights(KerasModelUtils.java:302)
	at org.deeplearning4j.nn.modelimport.keras.KerasModel.<init>(KerasModel.java:183)
	at org.deeplearning4j.nn.modelimport.keras.KerasModel.<init>(KerasModel.java:96)
	at org.deeplearning4j.nn.modelimport.

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from html.parser import HTMLParser
import urllib.request

# Get an HTML from URL
def getHTML(url):
	response = urllib.request.urlopen(url)
	return str(response.read())

# Searching sections #
found_table = False

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(* Graphic Library *)
#load "graphics.cma";;

module KDTrees :
  sig
		val getFormat : int -> int -> string
		val drawPoints : int array array -> unit
		val randomPoints : int * int -> int -> int array array
		val per_co_sort : 'a array array -> int -> int -> unit
		type 'a tree = EmptyTree | Node of 'a array * 'a tree * 'a tree

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(* Hamming Weight *)
(* Iterate everything *)
let rec hamming_weight_naive a =
	if a = 0 then 0
	else (a land 1) + (hamming_weight_naive (a lsr 1));;
(* Iterate as much time as there are 1-bits *)
let rec hamming_weight_sparse a =
	if a = 0 then 0
	else 1 + (hamming_weight_sparse (a land (a-1)));;
(* Get the size of the int *)

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def avg_bloc(matrix,a,b,bloc_size_h,bloc_size_w):
	# Generate coordonates and sum
	target = []
	sum_b = 0
	for i in range(-bloc_size_h/2,(bloc_size_h/2)):
		for j in range(-bloc_size_w/2,(bloc_size_w/2)):
			sum_b += matrix[a+i][b+j]
			target.append((a+i,b+j))
	# Remove pixels under average
	avg = (sum_b * 1.0) / (bloc_size_h * bloc_size_w)

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# Datas

# Configs
'''
CPU (AMD - AMD4) :
	* AMD Ryzen 5 1600X
	* AMD Ryzen 7 1700X
	* AMD Ryzen 7 1800X
CPU (AMD - AMD4 - 2nd Gen) :
	* AMD Ryzen 2600

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(* Circulate a list *)
let circulate l =
	let last = ref (List.hd l) in
	let rec circulate_aux l = match l with
		| [] -> failwith "cirulate: You shouldn't have come here!"
		| [a] -> 
				last := a;
				[]
		| h::t -> h::(circulate_aux t) in
	let tmp = circulate_aux l in

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From 31f072c192b9c09c3a80238951be897b69796c6a Mon Sep 17 00:00:00 2001
From: Louis Popi <theh2o64@gmail.com>
Date: Sun, 25 Mar 2018 20:19:41 +0200
Subject: [PATCH] biometrics: Open FP HAL based on fp_drv_info

---
 biometrics/BiometricsFingerprint.cpp | 91 +++++++++++++++++-------------------
 biometrics/BiometricsFingerprint.h   |  3 +-
 2 files changed, 43 insertions(+), 51 deletions(-)