ter = array_value($config, 'filter');
    $arr = array_value($filter, $type);
    $enable = array_value($arr, 'enable');
    $wordarr = array_value($arr, 'keyword');

    if (0 == $enable || empty($wordarr)) return FALSE;

    foreach ($wordarr as $_keyword) {
        if (!$_keyword) continue;
        $r = strpos(strtolower($keyword), strtolower($_keyword));
        if (FALSE !== $r) {
            $error = $_keyword;
            return TRUE;
        }
    }
    return FALSE;
}

// return http://domain.com OR https://domain.com
function url_prefix()
{
    $http = ((isset($_SERVER['HTTPS']) && 'on' == $_SERVER['HTTPS']) || (isset($_SERVER['HTTP_X_FORWARDED_PROTO']) && $_SERVER['HTTP_X_FORWARDED_PROTO'] == 'https')) ? 'https://' : 'http://';
    return $http . $_SERVER['HTTP_HOST'];
}

// 唯一身份ID
function uniq_id()
{
    return uniqid(substr(md5(microtime(true) . mt_rand(1000, 9999)), 8, 8));
}

// 生成订单号 14位
function trade_no()
{
    $trade_no = str_replace('.', '', microtime(1));
    $strlen = mb_strlen($trade_no, 'UTF-8');
    $strlen = 14 - $strlen;
    $str = '';
    if ($strlen) {
        for ($i = 0; $i <= $strlen; $i++) {
            if ($i < $strlen) $str .= '0';
        }
    }
    return $trade_no . $str;
}

// 生成订单号 16位
function trade_no_16()
{
    $explode = explode(' ', microtime());
    $trade_no = $explode[1] . mb_substr($explode[0], 2, 6, 'UTF-8');
    return $trade_no;
}

// 当前年的天数
function date_year($time = NULL)
{
    $time = intval($time) ? $time : time();
    return date('L', $time) + 365;
}

// 当前年份中的第几天
function date_z($time = NULL)
{
    $time = intval($time) ? $time : time();
    return date('z', $time);
}

// 当前月份中的第几天，没有前导零 1 到 31
function date_j($time = NULL)
{
    $time = intval($time) ? $time : time();
    return date('j', $time);
}

// 当前月份中的第几天，有前导零的2位数字 01 到 31
function date_d($time = NULL)
{
    $time = intval($time) ? $time : time();
    return date('d', $time);
}

// 当前时间为星期中的第几天 数字表示 1表示星期一 到 7表示星期天
function date_w_n($time = NULL)
{
    $time = intval($time) ? $time : time();
    return date('N', $time);
}

// 当前日第几周
function date_d_w($time = NULL)
{
    $time = intval($time) ? $time : time();
    return date('W', $time);
}

// 当前几月 没有前导零1-12
function date_n($time = NULL)
{
    $time = intval($time) ? $time : time();
    return date('n', $time);
}

// 当前月的天数
function date_t($time = NULL)
{
    $time = intval($time) ? $time : time();
    return date('t', $time);
}

// 0 o'clock on the day
function clock_zero()
{
    return strtotime(date('Ymd'));
}

// 24 o'clock on the day
function clock_twenty_four()
{
    return strtotime(date('Ymd')) + 86400;
}

// 8点过期 / expired at 8 a.m.
function eight_expired($time = NULL)
{
    $time = intval($time) ? $time : time();
    // 当前时间大于8点则改为第二天8点过期
    $life = date('G') <= 8 ? (strtotime(date('Ymd')) + 28800 - $time) : clock_twenty_four() - $time + 28800;
    return $life;
}

// 24点过期 / expired at 24 a.m.
function twenty_four_expired($time = NULL)
{
    $time = intval($time) ? $time : time();
    $twenty_four = clock_twenty_four();
    $life = $twenty_four - $time;
    return $life;
}

/**
 * @param $url 提交地址
 * @param string $post POST数组 / 空为GET获取数据 / $post='GET'获取连续跳转最终URL
 * @param string $cookie cookie
 * @param int $timeout 超时
 * @param int $ms 设为1是毫秒
 * @return mixed    返回数据
 */
function https_request($url, $post = '', $cookie = '', $timeout = 30, $ms = 0)
{
    if (empty($url)) return FALSE;

    if (version_compare(PHP_VERSION, '5.2.3', '<')) {
        $ms = 0;
        $timeout = 30;
    }

    is_array($post) and $post = http_build_query($post);

    // 没有安装curl 使用http的形式，支持post
    if (!extension_loaded('curl')) {
        //throw new Exception('server not install CURL');
        if ($post) {
            return https_post($url, $post, $cookie, $timeout);
        } else {
            return http_get($url, $cookie, $timeout);
        }
    }

    is_array($cookie) and $cookie = http_build_query($cookie);
    $curl = curl_init();
    // 返回执行结果，不输出
    curl_setopt($curl, CURLOPT_RETURNTRANSFER, true);
    //php5.5跟php5.6中的CURLOPT_SAFE_UPLOAD的默认值不同
    if (class_exists('\CURLFile')) {
        curl_setopt($curl, CURLOPT_SAFE_UPLOAD, true);
    } else {
        defined('CURLOPT_SAFE_UPLOAD') and curl_setopt($curl, CURLOPT_SAFE_UPLOAD, false);
    }
    // 设定请求的RUL
    curl_setopt($curl, CURLOPT_URL, $url);
    // 设定返回信息中包含响应信息头
    if (ini_get('safe_mode') && ini_get('open_basedir')) {
        // $post参数必须为GET
        if ('GET' == $post) {
            // 安全模式时将头文件的信息作为数据流输出
            curl_setopt($curl, CURLOPT_HEADER, true);
            // 安全模式采用连续抓取
            curl_setopt($curl, CURLOPT_NOBODY, true);
        }
    } else {
        curl_setopt($curl, CURLOPT_HEADER, false);
        // 允许跳转10次
        curl_setopt($curl, CURLOPT_MAXREDIRS, 10);
        // 使用自动跳转，返回最后的Location
        curl_setopt($curl, CURLOPT_FOLLOWLOCATION, true);
    }
    $ua1 = 'Mozilla/5.0 (iPhone; CPU iPhone OS 13_2_3 like Mac OS X) AppleWebKit/605.1.15 (KHTML, like Gecko) Version/13.0.3 Mobile/15E148 Safari/604.1';
    $ua = empty($_SERVER["HTTP_USER_AGENT"]) ? $ua1 : $_SERVER["HTTP_USER_AGENT"];
    curl_setopt($curl, CURLOPT_USERAGENT, $ua);
    // 兼容HTTPS
    if (FALSE !== stripos($url, 'https://')) {
        curl_setopt($curl, CURLOPT_SSL_VERIFYPEER, FALSE);
        curl_setopt($curl, CURLOPT_SSL_VERIFYHOST, FALSE);
        //ssl版本控制
        //curl_setopt($curl, CURLOPT_SSLVERSION, CURL_SSLVERSION_TLSv1);
        curl_setopt($curl, CURLOPT_SSLVERSION, true);
    }

    $header = array('Content-type: application/x-www-form-urlencoded;charset=UTF-8', 'X-Requested-With: XMLHttpRequest');
    $cookie and $header[] = "Cookie: $cookie";
    curl_setopt($curl, CURLOPT_HTTPHEADER, $header);

    if ($post) {
        // POST
        curl_setopt($curl, CURLOPT_POST, true);
        // 自动设置Referer
        curl_setopt($curl, CURLOPT_AUTOREFERER, true);
        curl_setopt($curl, CURLOPT_POSTFIELDS, $post);
    }

    if ($ms) {
        curl_setopt($curl, CURLOPT_NOSIGNAL, true); // 设置毫秒超时
        curl_setopt($curl, CURLOPT_TIMEOUT_MS, intval($timeout)); // 超时毫秒
    } else {
        curl_setopt($curl, CURLOPT_TIMEOUT, intval($timeout)); // 秒超时
    }
    //优先解析 IPv6 超时后IPv4
    //curl_setopt($curl, CURLOPT_IPRESOLVE, CURL_IPRESOLVE_V4);
    curl_setopt($curl, CURLOPT_ENCODING, 'gzip');
    // 返回执行结果
    $output = curl_exec($curl);
    // 有效URL，输出URL非URL页面内容 CURLOPT_RETURNTRANSFER 必须为false
    'GET' == $post and $output = curl_getinfo($curl, CURLINFO_EFFECTIVE_URL);
    curl_close($curl);
    return $output;
}

function save_image($img)
{
    $ch = curl_init();
    // 设定请求的RUL
    curl_setopt($ch, CURLOPT_URL, $img);
    // 设定返回信息中包含响应信息头 启用时会将头文件的信息作为数据流输出
    //curl_setopt($ch, CURLOPT_HEADER, false);
    //curl_setopt($ch, CURLOPT_USERAGENT, $_SERVER["HTTP_USER_AGENT"]);
    // true表示$html,false表示echo $html
    curl_setopt($ch, CURLOPT_RETURNTRANSFER, true);
    curl_setopt($ch, CURLOPT_CONNECTTIMEOUT, 10);
    curl_setopt($ch, CURLOPT_SSL_VERIFYHOST, false);
    curl_setopt($ch, CURLOPT_SSL_VERIFYPEER, false);
    //curl_setopt($ch, CURLOPT_BINARYTRANSFER, 1);
    //curl_setopt($ch, CURLOPT_FOLLOWLOCATION, 0);
    curl_setopt($ch, CURLOPT_ENCODING, 'gzip');
    $output = curl_exec($ch);
    curl_close($ch);
    return $output;
}

// 计算字串宽度:剧中对齐(字体大小/字串内容/字体链接/背景宽度/倍数)
function calculate_str_width($size, $str, $font, $width, $multiple = 2)
{
    $box = imagettfbbox($size, 0, $font, $str);
    return ($width - $box[4] - $box[6]) / $multiple;
}

// 搜索目录下的文件 比对文件后缀
function search_directory($path)
{
    if (is_dir($path)) {
        $paths = scandir($path);
        foreach ($paths as $val) {
            $sub_path = $path . '/' . $val;
            if ('.' == $val || '..' == $val) {
                continue;
            } else if (is_dir($sub_path)) {
                //echo '目录名:' . $val . '<br/>';
                search_directory($sub_path);
            } else {
                //echo ' 最底层文件: ' . $path . '/' . $val . ' <hr/>';
                $ext = strtolower(file_ext($sub_path));
                if (in_array($ext, array('php', 'asp', 'jsp', 'cgi', 'exe', 'dll'), TRUE)) {
                    echo '异常文件：' . $sub_path . ' <hr/>';
                }
            }
        }
    }
}

// 一维数组转字符串 $sign待签名字符串 $url为urlencode转码GET参数字符串
function array_to_string($arr, &$sign = '', &$url = '')
{
    if (count($arr) != count($arr, 1)) throw new Exception('Does not support multi-dimensional array to string');

    // 注销签名
    unset($arr['sign']);

    // 排序
    ksort($arr);
    reset($arr);

    // 转字符串做签名
    $url = '';
    $sign = '';
    foreach ($arr as $key => $val) {
        if (empty($val) || is_array($val)) continue;
        $url .= $key . '=' . urlencode($val) . '&';
        $sign .= $key . '=' . $val . '&';
    }
    $url = substr($url, 0, -1);
    $url = htmlspecialchars($url);
    $sign = substr($sign, 0, -1);
}

// 私钥生成签名
function rsa_create_sign($data, $key, $sign_type = 'RSA')
{
    if (!function_exists('openssl_sign')) throw new Exception('OpenSSL extension is not enabled');

    if (!defined('OPENSSL_ALGO_SHA256')) throw new Exception('Only versions above PHP 5.4.8 support SHA256');

    $key = wordwrap($key, 64, "\n", true);
    if (FALSE === $key) throw new Exception('Private Key Error');

    $key = "-----BEGIN RSA PRIVATE KEY-----\n$key\n-----END RSA PRIVATE KEY-----";

    if ('RSA2' == $sign_type) {
        openssl_sign($data, $sign, $key, OPENSSL_ALGO_SHA256);
    } else {
        openssl_sign($data, $sign, $key, OPENSSL_ALGO_SHA1);
    }

    // 加密
    return base64_encode($sign);
}

// 公钥验证签名
function rsa_verify_sign($data, $sign, $key, $sign_type = 'RSA')
{
    $key = wordwrap($key, 64, "\n", true);
    if (FALSE === $key) throw new Exception('Public Key Error');

    $key = "-----BEGIN PUBLIC KEY-----\n$key\n-----END PUBLIC KEY-----";

    // 签名正确返回1 签名不正确返回0 错误-1
    if ('RSA2' == $sign_type) {
        $result = openssl_verify($data, base64_decode($sign), $key, OPENSSL_ALGO_SHA256);
    } else {
        $result = openssl_verify($data, base64_decode($sign), $key, OPENSSL_ALGO_SHA1);
    }

    return $result === 1;
}

// Array to xml array('appid' => 'appid', 'code' => 'success')
function array_to_xml($arr)
{
    if (!is_array($arr) || empty($arr)) throw new Exception('Array Error');

    $xml = "<xml>";
    foreach ($arr as $key => $val) {
        if (is_numeric($val)) {
            $xml .= "<" . $key . ">" . $val . "</" . $key . ">";
        } else {
            $xml .= "<" . $key . "><![CDATA[" . $val . "]]></" . $key . ">";
        }
    }
    $xml .= "</xml>";
    return $xml;
}

// Xml to array
function xml_to_array($xml)
{
    if (!$xml) throw new Exception('XML error');

    $old = libxml_disable_entity_loader(true);

    // xml解析
    $result = (array)simplexml_load_string($xml, null, LIBXML_NOCDATA | LIBXML_COMPACT);
    // 恢复旧值
    if (FALSE === $old) libxml_disable_entity_loader(false);

    return $result;
}

// 逐行读取
function well_import($file)
{
    if ($handle = fopen($file, 'r')) {
        while (!feof($handle)) {
            yield trim(fgets($handle));
        }
        fclose($handle);
    }
}

// 计算总行数
function well_import_total($file, $key = 'well_import_total')
{
    static $cache = array();
    if (isset($cache[$key])) return $cache[$key];
    $count = cache_get($key);
    if (NULL === $count) {
        $count = 0;
        $globs = well_import($file);
        while ($globs->valid()) {
            ++$count;
            $globs->next(); // 指向下一个
        }
        $count and cache_set($key, $count, 300);
    }

    return $cache[$key] = $count;
}

$g_dir_file = FALSE;
function well_search_dir($path)
{
    global $g_dir_file;
    FALSE === $g_dir_file and $g_dir_file = array();
    if (is_dir($path)) {
        $paths = scandir($path);
        foreach ($paths as $val) {
            $sub_path = $path . '/' . $val;
            if ('.' == $val || '..' == $val) {
                continue;
            } else if (is_dir($sub_path)) {
                well_search_dir($sub_path);
            } else {
                $g_dir_file[] = $sub_path;
            }

        }
    }

    return $g_dir_file;
}




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<a href="/">首页</a><small>&gt;</small><a href="/programmer">programmer</a><small>&gt;</small><span class="muted">onnx - How could I draw bbox from output of YOLOV8 Quantized from Qualcomm SNPE (Inferenced by Hexagon DSP under uint8) - Stack </span></div><header class="article-header"><h1 class="article-title"><a href="http://www.815494.com/programmer/1743947249a2321604.html">onnx - How could I draw bbox from output of YOLOV8 Quantized from Qualcomm SNPE (Inferenced by Hexagon DSP under uint8) - Stack </a></h1><div class="meta"><span class="muted"><a href="/programmer"><i class="icon-list-alt icon12"></i>programmer</a></span><span class="muted"><i class="icon-user icon12"></i><a href="/user/1.html">admin</a></span><time class="muted"><i class="ico icon-time icon12"></i>2025-04-06</time><span class="muted"><i class="ico icon-eye-open icon12"></i>3浏览</span><span class="muted"><i class="icon-comment icon12"></i><a href="#comments">0评论</a></span></div></header><article class="article-content"><p>I have a yolov8s model for object detection (2 classes). I converted yolov8s.onnx to yolov8s.dlc by this command:</p>
<pre><code>python $SNPE_ROOT/bin/x86_64-linux-clang/snpe-onnx-to-dlc \
  --input_network yolov8s.onnx \
  --input_type images image \
  --input_layout images NCHW \
  --input_dim images &quot;1, 3, 640, 640&quot; \
  --input_dtype images float32 \
  --input_encoding images bgr \
  --out_node output0 \
  --output_path yolov8s.dlc
</code></pre>
<p>After that, I continue to quantized yolov8s.dlc to yolov8s_quantize.dlc:</p>
<pre><code>source $SNPE_ROOT/bin/x86_64-linux-clang/snpe-dlc-quantize \
   --input_dlc yolov8s.dlc \
   --input_list raw_list.txt \
   --output_dlc yolov8s_quantized.dlc
</code></pre>
<p>My raw images format is NCHW, float32, normalize by divided by 255.</p>
<p>I use one of raw images to reference:</p>
<pre><code>$SNPE_ROOT/bin/aarch64-ubuntu-gcc9.4/snpe-net-run \
   --input_list input.txt \
   --container yolov8s_quantized.dlc \
   --output_dir output \
   --use_dsp
</code></pre>
<p>I got the output is a raw file. Thus, how I can draw bbox from this raw file to sample image.</p>
<p>I try to find scale and offset of current quantized model by using <code>snpe-dlc-info -i yolov8_quantized.dlc</code>. I got this:</p>
<pre><code>-------------------------------------------------------------------------------------------------------------------------------------------
| Input Name  | Dimensions   | Type    | Encoding Info
                  |
-------------------------------------------------------------------------------------------------------------------------------------------
| images      | 1,640,640,3  | uFxp_8  | bitwidth 8, min 0.000000000000, max 1.000000000000, scale 0.003921568859, offset 0.000000000000  |
-------------------------------------------------------------------------------------------------------------------------------------------
-------------------------------------------------------------------------------------------------------------------------------------------------
| Output Name  | Dimensions  | Type    | Encoding Info
                        |
-------------------------------------------------------------------------------------------------------------------------------------------------
| output0      | 1,6,8400    | uFxp_8  | bitwidth 8, min -43.135402679443, max 690.166442871094, scale 2.875693559647, offset -15.000000000000  |
-------------------------------------------------------------------------------------------------------------------------------------------------
</code></pre>
<p>Then I use this formula <code>dequant_output = quant_output * SCALE - OFFSET</code> with <code>SCALE =  2.875693559647</code>, <code>OFFSET = -15</code> to get the value to draw bbox on image. But it have high confidences score. I couldn't draw exactly bbox for objects.</p>
    
                
<p>I have a yolov8s model for object detection (2 classes). I converted yolov8s.onnx to yolov8s.dlc by this command:</p>
<pre><code>python $SNPE_ROOT/bin/x86_64-linux-clang/snpe-onnx-to-dlc \
  --input_network yolov8s.onnx \
  --input_type images image \
  --input_layout images NCHW \
  --input_dim images &quot;1, 3, 640, 640&quot; \
  --input_dtype images float32 \
  --input_encoding images bgr \
  --out_node output0 \
  --output_path yolov8s.dlc
</code></pre>
<p>After that, I continue to quantized yolov8s.dlc to yolov8s_quantize.dlc:</p>
<pre><code>source $SNPE_ROOT/bin/x86_64-linux-clang/snpe-dlc-quantize \
   --input_dlc yolov8s.dlc \
   --input_list raw_list.txt \
   --output_dlc yolov8s_quantized.dlc
</code></pre>
<p>My raw images format is NCHW, float32, normalize by divided by 255.</p>
<p>I use one of raw images to reference:</p>
<pre><code>$SNPE_ROOT/bin/aarch64-ubuntu-gcc9.4/snpe-net-run \
   --input_list input.txt \
   --container yolov8s_quantized.dlc \
   --output_dir output \
   --use_dsp
</code></pre>
<p>I got the output is a raw file. Thus, how I can draw bbox from this raw file to sample image.</p>
<p>I try to find scale and offset of current quantized model by using <code>snpe-dlc-info -i yolov8_quantized.dlc</code>. I got this:</p>
<pre><code>-------------------------------------------------------------------------------------------------------------------------------------------
| Input Name  | Dimensions   | Type    | Encoding Info
                  |
-------------------------------------------------------------------------------------------------------------------------------------------
| images      | 1,640,640,3  | uFxp_8  | bitwidth 8, min 0.000000000000, max 1.000000000000, scale 0.003921568859, offset 0.000000000000  |
-------------------------------------------------------------------------------------------------------------------------------------------
-------------------------------------------------------------------------------------------------------------------------------------------------
| Output Name  | Dimensions  | Type    | Encoding Info
                        |
-------------------------------------------------------------------------------------------------------------------------------------------------
| output0      | 1,6,8400    | uFxp_8  | bitwidth 8, min -43.135402679443, max 690.166442871094, scale 2.875693559647, offset -15.000000000000  |
-------------------------------------------------------------------------------------------------------------------------------------------------
</code></pre>
<p>Then I use this formula <code>dequant_output = quant_output * SCALE - OFFSET</code> with <code>SCALE =  2.875693559647</code>, <code>OFFSET = -15</code> to get the value to draw bbox on image. But it have high confidences score. I couldn't draw exactly bbox for objects.</p>
    

        
            
                
                    
                    <ul class='ml0 list-ls-none js-post-tag-list-wrapper d-inline'><li class='d-inline mr4 js-post-tag-list-item'>onnx</li><li class='d-inline mr4 js-post-tag-list-item'>yolov8</li><li class='d-inline mr4 js-post-tag-list-item'>qualcomm</li><li class='d-inline mr4 js-post-tag-list-item'>snpe</li></ul>
                
            
        

    
        
            
                




    

        
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            asked <span title='2025-03-31 12:38:29Z' class='relativetime'>Mar 31 at 12:38</span>
        
        
    
    
        
    
    
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<p>The output from snpe-net-run is already de-quantized to float32. This is the equivalent raw buffer from the ONNX equivalent which can be taken for post-processing to extract the bounding boxes.</p>
<p>You may further refer to the following resource to understand the inference flow with Yolov8 using SNPE,</p>
<p>https://github/quic/qidk/blob/master/Model-Enablement/Model-Accuracy-Mixed-Precision/Accuracy_Analyzer_YoloV8.ipynb</p></article><footer class="article-footer"><div class="article-tags">
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