symisc

import requests
import json

# Detect all human faces & extract their facial landmarks via `facelandmarks`.
# Once done, mimic the famous Snapchat flower crown filter.
# Only three commands are actually needed in order to mimic the Snapchat filters:
# face landmarks:         https://pixlab.io/cmd?id=facelandmarks
# smart resize:           https://pixlab.io/cmd?id=smartresize
# merge:                  https://pixlab.io/cmd?id=merge
# Optionally: blur, grayscale, drawtext, oilpaint, etc. for cool background effects.

symisc

import requests
import json

# Mimic the two famous Snapchat filters: The flower crown & the dog facial parts filter.
# The target image must contain at least one human face. The more faces you got, the more funny it should be!
# 
# Only three commands are actually needed in order to mimic the Snapchat filters:
# face landmarks:         https://pixlab.io/cmd?id=facelandmarks
# smart resize:           https://pixlab.io/cmd?id=smartresize
# merge:                  https://pixlab.io/cmd?id=merge

symisc

import requests
import json
	
# Make an eye mask plus a mustache filter and finally draw some text on the bottom of the image.
# 
# Only three commands are actually needed in order to mimic the Snapchat filters:
# face landmarks:         https://pixlab.io/#/cmd?id=facelandmarks
# smart resize:           https://pixlab.io/#/cmd?id=smartresize
# merge:                  https://pixlab.io/#/cmd?id=merge
# rotate (Optionally):    https://pixlab.io/#/cmd?id=rotate

symisc

<?php
 
//////////////////////////////////
// Reddit "hot" story algorithm //
//////////////////////////////////
function hot($ups, $downs, $date)
{
	if (is_string($date)) $date = strtotime($date);
 
	$s = $ups - $downs;

symisc

<?php
/*
 * PixLab PHP Client which is just a single class PHP file without any dependency that you can get from Github
 * https://github.com/symisc/pixlab-php 
 */
require_once "pixlab.php";

# Target Image: Change to any link (Possibly adult) you want or switch to POST if you want to upload your image directly, refer to the sample set for more info.
$img = 'https://i.redd.it/oetdn9wc13by.jpg';
# Your PixLab key

symisc

#include <stdio.h>
#include <assert.h>

int main(int argc, char** argv) {
	assert(argc == 2);
	char* fn = argv[1];
	FILE* f = fopen(fn, "r");
	printf("char a[] = {\n");
	unsigned long n = 0;
	while(!feof(f)) {

symisc

<?php
/*
 * PixLab PHP Client which is just a single class PHP file without any dependency that you can get from Github
 * https://github.com/symisc/pixlab-php 
 */
require_once "pixlab.php";

# Given an image with human readable characters. Detect input language & extract text content from there.
# https://pixlab.io/#/cmd?id=ocr for additional information.

symisc

import requests
import json
# Colorize this 1933 picture of this little girl via: https://pixlab.io/cmd?id=colorize
req = requests.get('https://api.pixlab.io/colorize',params={'img':'https://i.redd.it/7z1q27vaa9tz.png','key':'My_PixLab_Key'})
reply = req.json()
if reply['status'] != 200:
    print (reply['error'])
else:
print ("Link to the colorized picture: "+ reply['link'])

symisc

/*
 * Programming introduction with the SOD Embedded Convolutional/Recurrent Neural Networks (CNN/RNN) API.
 * Copyright (C) PixLab | Symisc Systems, https://sod.pixlab.io
 */
/*
* Compile this file together with the SOD embedded source code to generate
* the executable. For example:
*
*  gcc sod.c cnn_object_detection.c -lm -Ofast -march=native -Wall -std=c99 -o sod_cnn_intro
*  

symisc

/*
 * Programming introduction with the SOD Embedded RealNets Model Training API.
 * Training must be enabled via the compile-time directive SOD_ENABLE_NET_TRAIN.
 *
 * Copyright (C) PixLab | Symisc Systems, https://sod.pixlab.io
 */
/*
* Compile this file together with the SOD embedded source code to generate
* the executable. For example:
*