added readNetFromTensorflow, changed blobFromImage method to function like in c++/python

Author: morozovsk

opencv.cc

@@ -125,7 +125,7 @@ PHP_MINIT_FUNCTION(opencv)
 	opencv_objdetect_init(module_number);
 	opencv_videoio_init(module_number);
     opencv_face_init(module_number);
-    opencv_dnn_net_init(module_number);
+    opencv_dnn_init(module_number);
 	opencv_ml_init(module_number);
     opencv_cvdef_init(module_number);
 
@@ -246,6 +246,10 @@ const zend_function_entry opencv_functions[] = {
     ZEND_NS_NAMED_FE(OPENCV_NS, findContoursWithoutHierarchy, ZEND_FN(opencv_find_contours_without_hierarchy), opencv_find_contours_without_hierarchy_arginfo)
     ZEND_NS_NAMED_FE(OPENCV_NS, drawContours, ZEND_FN(opencv_draw_contours), opencv_draw_contours_arginfo)
     ZEND_NS_NAMED_FE(OPENCV_NS, boundingRect, ZEND_FN(opencv_bounding_rect), NULL)
+    ZEND_NS_NAMED_FE(OPENCV_DNN_NS, blobFromImage, ZEND_FN(opencv_dnn_blob_from_image), NULL)
+    ZEND_NS_NAMED_FE(OPENCV_DNN_NS, readNetFromCaffe, ZEND_FN(opencv_dnn_read_net_from_caffe), NULL)
+    ZEND_NS_NAMED_FE(OPENCV_DNN_NS, readNetFromTorch, ZEND_FN(opencv_dnn_read_net_from_torch), NULL)
+    ZEND_NS_NAMED_FE(OPENCV_DNN_NS, readNetFromTensorflow, ZEND_FN(opencv_dnn_read_net_from_tensorflow), NULL)
 	PHP_FE_END	/* Must be the last line in opencv_functions[] */
 };
 /* }}} */

source/opencv2/core/opencv_mat.cc

@@ -220,6 +220,12 @@ PHP_METHOD(opencv_mat, channels)
     RETURN_LONG(obj->mat->channels());
 }
 
+PHP_METHOD(opencv_mat, total)
+{
+    opencv_mat_object *obj = Z_PHP_MAT_OBJ_P(getThis());
+    RETURN_LONG(obj->mat->total());
+}
+
 PHP_METHOD(opencv_mat, empty)
 {
     opencv_mat_object *obj = Z_PHP_MAT_OBJ_P(getThis());
@@ -505,12 +511,12 @@ PHP_METHOD(opencv_mat, at)
  */
 PHP_METHOD(opencv_mat, atIdx) // multi dimensions support
 {
-    long channel;
+    long channel = 1;
     zval *value_zval = NULL;
     zval *idx_zval;
     int *idx = nullptr;
 
-    if (zend_parse_parameters_ex(ZEND_PARSE_PARAMS_QUIET, ZEND_NUM_ARGS(), "al|z", &idx_zval, &channel, &value_zval) == FAILURE) {
+    if (zend_parse_parameters_ex(ZEND_PARSE_PARAMS_QUIET, ZEND_NUM_ARGS(), "a|lz", &idx_zval, &channel, &value_zval) == FAILURE) {
         RETURN_NULL();
     }
 

source/opencv2/dnn/opencv_dnn.cc

@@ -47,7 +47,7 @@ zend_class_entry *opencv_dnn_net_ce;
 
 zend_class_entry *opencv_base_dnn_net_ce;
 
-PHP_METHOD(opencv_dnn_net, blobFromImage)
+PHP_FUNCTION(opencv_dnn_blob_from_image)
 {
     zval *image_zval, *size_zval, *mean_zval;
     double scalefactor = 1.;
@@ -78,7 +78,7 @@ PHP_METHOD(opencv_dnn_net, blobFromImage)
     RETURN_ZVAL(&instance,0,0); //return php Mat object
 }
 
-PHP_METHOD(opencv_dnn_net, readNetFromTorch)
+PHP_FUNCTION(opencv_dnn_read_net_from_torch)
 {
     char *filename;
     size_t filename_len;
@@ -94,12 +94,7 @@ PHP_METHOD(opencv_dnn_net, readNetFromTorch)
     RETURN_ZVAL(&instance,0,0);
 }
 
-ZEND_BEGIN_ARG_INFO_EX(opencv_dnn_net_readNetFromCaffe_arginfo, 0, 0, 2)
-                ZEND_ARG_INFO(0, prototxt)
-                ZEND_ARG_INFO(0, caffeModel)
-ZEND_END_ARG_INFO()
-
-PHP_METHOD(opencv_dnn_net, readNetFromCaffe)
+PHP_FUNCTION(opencv_dnn_read_net_from_caffe)
 {
     char *prototxt, *caffeModel;
     size_t prototxt_len, caffeModel_len;
@@ -129,6 +124,36 @@ PHP_METHOD(opencv_dnn_net, readNetFromCaffe)
     RETURN_ZVAL(&instance,0,0);
 }
 
+PHP_FUNCTION(opencv_dnn_read_net_from_tensorflow)
+{
+    char *model, *config;
+    size_t model_len, config_len;
+    if (zend_parse_parameters(ZEND_NUM_ARGS(), "ss", &model, &model_len, &config, &config_len) == FAILURE) {
+        RETURN_NULL();
+    }
+
+    ifstream modelFile;
+    modelFile.open(model);//open the input file
+    stringstream modelStream;
+    modelStream << modelFile.rdbuf();//read the file
+    string modelData = modelStream.str();
+
+    ifstream configFile;
+    configFile.open(config, ios::binary);//open the input file
+    stringstream configStream;
+    configStream << configFile.rdbuf();//read the file
+    string configData = configStream.str();
+
+    zval instance;
+    object_init_ex(&instance, opencv_dnn_net_ce);
+    opencv_dnn_net_object *obj = Z_PHP_DNN_NET_OBJ_P(&instance);
+
+    //obj->DNNNet = readNetFromTensorflow(modelData.c_str(), modelData.size());
+    obj->DNNNet = readNetFromTensorflow(modelData.c_str(), modelData.size(), configData.c_str(), configData.size());
+
+    RETURN_ZVAL(&instance,0,0);
+}
+
 PHP_METHOD(opencv_dnn_net, setInput)
 {
     zval *image_zval;
@@ -168,9 +193,6 @@ PHP_METHOD(opencv_dnn_net, forward)
  * opencv_dnn_net_methods[]
  */
 const zend_function_entry opencv_dnn_net_methods[] = {
-        PHP_ME(opencv_dnn_net, blobFromImage, NULL, ZEND_ACC_PUBLIC|ZEND_ACC_STATIC)
-        PHP_ME(opencv_dnn_net, readNetFromTorch, NULL, ZEND_ACC_PUBLIC|ZEND_ACC_STATIC)
-        PHP_ME(opencv_dnn_net, readNetFromCaffe, NULL, ZEND_ACC_PUBLIC|ZEND_ACC_STATIC)
         PHP_ME(opencv_dnn_net, setInput, NULL, ZEND_ACC_PUBLIC)
         PHP_ME(opencv_dnn_net, forward, NULL, ZEND_ACC_PUBLIC)
         PHP_FE_END
@@ -193,7 +215,7 @@ zend_object* opencv_dnn_net_handler(zend_class_entry *type)
     return &obj->std;
 }
 
-void opencv_dnn_net_init(int module_number){
+void opencv_dnn_init(int module_number){
     zend_class_entry ce;
     INIT_NS_CLASS_ENTRY(ce,OPENCV_DNN_NS, "Net", opencv_dnn_net_methods);
     opencv_dnn_net_ce = zend_register_internal_class_ex(&ce, opencv_dnn_net_ce);
@@ -204,7 +226,7 @@ void opencv_dnn_net_init(int module_number){
 
 #else
 
-void opencv_dnn_net_init(int module_number){
+void opencv_dnn_init(int module_number){
 
 }
 

source/opencv2/dnn/opencv_dnn.h

@@ -24,6 +24,10 @@
 #include <streambuf>
 
 
-extern void opencv_dnn_net_init(int module_number);
+extern void opencv_dnn_init(int module_number);
 
 #endif
+PHP_FUNCTION(opencv_dnn_blob_from_image);
+PHP_FUNCTION(opencv_dnn_read_net_from_torch);
+PHP_FUNCTION(opencv_dnn_read_net_from_caffe);
+PHP_FUNCTION(opencv_dnn_read_net_from_tensorflow);

tests/dnn.phpt

@@ -9,7 +9,7 @@ use function CV\{imread};
 
 $src = imread("./tests/Obama_gray.png");
 
-$blob = \CV\DNN\Net::blobFromImage($src, 1, new \CV\Size(48, 48), new Scalar(104, 177, 123));
+$blob = \CV\DNN\blobFromImage($src, 1, new \CV\Size(48, 48), new Scalar(104, 177, 123));
 var_export($blob);
 ?>
 --EXPECT--