fix(examples): load_param always failed (Tencent#4001)

examples/fasterrcnn.cpp

@@ -127,9 +127,9 @@ static int detect_fasterrcnn(const cv::Mat& bgr, std::vector<Object>& objects)
     // https://dl.dropboxusercontent.com/s/o6ii098bu51d139/faster_rcnn_models.tgz?dl=0
     // ZF_faster_rcnn_final.caffemodel
     // the ncnn model https://github.com/nihui/ncnn-assets/tree/master/models
-    if (!fasterrcnn.load_param("ZF_faster_rcnn_final.param"))
+    if (fasterrcnn.load_param("ZF_faster_rcnn_final.param"))
         exit(-1);
-    if (!fasterrcnn.load_model("ZF_faster_rcnn_final.bin"))
+    if (fasterrcnn.load_model("ZF_faster_rcnn_final.bin"))
         exit(-1);
 
     // hyper parameters taken from

examples/mobilenetssd.cpp

@@ -40,9 +40,9 @@ static int detect_mobilenet(const cv::Mat& bgr, std::vector<Object>& objects)
     // model is converted from https://github.com/chuanqi305/MobileNet-SSD
     // and can be downloaded from https://drive.google.com/open?id=0ByaKLD9QaPtucWk0Y0dha1VVY0U
     // the ncnn model https://github.com/nihui/ncnn-assets/tree/master/models
-    if (!mobilenet.load_param("mobilenet_ssd_voc_ncnn.param"))
+    if (mobilenet.load_param("mobilenet_ssd_voc_ncnn.param"))
         exit(-1);
-    if (!mobilenet.load_model("mobilenet_ssd_voc_ncnn.bin"))
+    if (mobilenet.load_model("mobilenet_ssd_voc_ncnn.bin"))
         exit(-1);
 
     const int target_size = 300;

examples/mobilenetv2ssdlite.cpp

@@ -47,9 +47,9 @@ static int detect_mobilenetv2(const cv::Mat& bgr, std::vector<Object>& objects)
     // original pretrained model from https://github.com/chuanqi305/MobileNetv2-SSDLite
     // https://github.com/chuanqi305/MobileNetv2-SSDLite/blob/master/ssdlite/voc/deploy.prototxt
     // the ncnn model https://github.com/nihui/ncnn-assets/tree/master/models
-    if (!mobilenetv2.load_param("mobilenetv2_ssdlite_voc.param"))
+    if (mobilenetv2.load_param("mobilenetv2_ssdlite_voc.param"))
         exit(-1);
-    if (!mobilenetv2.load_model("mobilenetv2_ssdlite_voc.bin"))
+    if (mobilenetv2.load_model("mobilenetv2_ssdlite_voc.bin"))
         exit(-1);
 
     const int target_size = 300;

examples/mobilenetv3ssdlite.cpp

@@ -51,9 +51,9 @@ static int detect_mobilenetv3(const cv::Mat& bgr, std::vector<Object>& objects)
 #endif // NCNN_VULKAN
 
     // converted ncnn model from https://github.com/ujsyehao/mobilenetv3-ssd
-    if (!mobilenetv3.load_param("./mobilenetv3_ssdlite_voc.param"))
+    if (mobilenetv3.load_param("./mobilenetv3_ssdlite_voc.param"))
         exit(-1);
-    if (!mobilenetv3.load_model("./mobilenetv3_ssdlite_voc.bin"))
+    if (mobilenetv3.load_model("./mobilenetv3_ssdlite_voc.bin"))
         exit(-1);
 
     const int target_size = 300;

examples/nanodet.cpp

@@ -226,9 +226,9 @@ static int detect_nanodet(const cv::Mat& bgr, std::vector<Object>& objects)
 
     // original pretrained model from https://github.com/RangiLyu/nanodet
     // the ncnn model https://github.com/nihui/ncnn-assets/tree/master/models
-    if (!nanodet.load_param("nanodet_m.param"))
+    if (nanodet.load_param("nanodet_m.param"))
         exit(-1);
-    if (!nanodet.load_model("nanodet_m.bin"))
+    if (nanodet.load_model("nanodet_m.bin"))
         exit(-1);
 
     int width = bgr.cols;

examples/nanodetplus_pnnx.cpp

@@ -226,9 +226,9 @@ static int detect_nanodet(const cv::Mat& bgr, std::vector<Object>& objects)
     // the ncnn model https://github.com/nihui/ncnn-assets/tree/master/models
     //     nanodet.load_param("nanodet-plus-m_320.torchscript.ncnn.param");
     //     nanodet.load_model("nanodet-plus-m_320.torchscript.ncnn.bin");
-    if (!nanodet.load_param("nanodet-plus-m_416.torchscript.ncnn.param"))
+    if (nanodet.load_param("nanodet-plus-m_416.torchscript.ncnn.param"))
         exit(-1);
-    if (!nanodet.load_model("nanodet-plus-m_416.torchscript.ncnn.bin"))
+    if (nanodet.load_model("nanodet-plus-m_416.torchscript.ncnn.bin"))
         exit(-1);
 
     int width = bgr.cols;

examples/p2pnet.cpp

@@ -156,9 +156,9 @@ static int detect_crowd(const cv::Mat& bgr, std::vector<CrowdPoint>& crowd_point
     // model is converted from
     // https://github.com/TencentYoutuResearch/CrowdCounting-P2PNet
     // the ncnn model  https://pan.baidu.com/s/1O1CBgvY6yJkrK8Npxx3VMg pwd: ezhx
-    if (!net.load_param("p2pnet.param"))
+    if (net.load_param("p2pnet.param"))
         exit(-1);
-    if (!net.load_model("p2pnet.bin"))
+    if (net.load_model("p2pnet.bin"))
         exit(-1);
 
     int width = bgr.cols;

examples/peleenetssd_seg.cpp

@@ -40,9 +40,9 @@ static int detect_peleenet(const cv::Mat& bgr, std::vector<Object>& objects, ncn
     // model is converted from https://github.com/eric612/MobileNet-YOLO
     // and can be downloaded from https://drive.google.com/open?id=1Wt6jKv13sBRMHgrGAJYlOlRF-o80pC0g
     // the ncnn model https://github.com/nihui/ncnn-assets/tree/master/models
-    if (!peleenet.load_param("pelee.param"))
+    if (peleenet.load_param("pelee.param"))
         exit(-1);
-    if (!peleenet.load_model("pelee.bin"))
+    if (peleenet.load_model("pelee.bin"))
         exit(-1);
 
     const int target_size = 304;

examples/retinaface.cpp

@@ -248,9 +248,9 @@ static int detect_retinaface(const cv::Mat& bgr, std::vector<FaceObject>& faceob
     // the ncnn model https://github.com/nihui/ncnn-assets/tree/master/models
     //     retinaface.load_param("retinaface-R50.param");
     //     retinaface.load_model("retinaface-R50.bin");
-    if (!retinaface.load_param("mnet.25-opt.param"))
+    if (retinaface.load_param("mnet.25-opt.param"))
         exit(-1);
-    if (!retinaface.load_model("mnet.25-opt.bin"))
+    if (retinaface.load_model("mnet.25-opt.bin"))
         exit(-1);
 
     const float prob_threshold = 0.8f;

examples/rfcn.cpp

@@ -126,9 +126,9 @@ static int detect_rfcn(const cv::Mat& bgr, std::vector<Object>& objects)
     // https://github.com/YuwenXiong/py-R-FCN/blob/master/models/pascal_voc/ResNet-50/rfcn_end2end/test_agnostic.prototxt
     // https://1drv.ms/u/s!AoN7vygOjLIQqUWHpY67oaC7mopf
     // resnet50_rfcn_final.caffemodel
-    if (!rfcn.load_param("rfcn_end2end.param"))
+    if (rfcn.load_param("rfcn_end2end.param"))
         exit(-1);
-    if (!rfcn.load_model("rfcn_end2end.bin"))
+    if (rfcn.load_model("rfcn_end2end.bin"))
         exit(-1);
 
     const int target_size = 224;

examples/rvm.cpp

@@ -47,9 +47,9 @@ static int detect_rvm(const cv::Mat& bgr, cv::Mat& pha, cv::Mat& fgr)
     net.opt.use_vulkan_compute = false;
     //original pretrained model from https://github.com/PeterL1n/RobustVideoMatting
     //ncnn model https://pan.baidu.com/s/11iEY2RGfzWFtce8ue7T3JQ password: d9t6
-    if (!net.load_param("rvm_512.param"))
+    if (net.load_param("rvm_512.param"))
         exit(-1);
-    if (!net.load_model("rvm_512.bin"))
+    if (net.load_model("rvm_512.bin"))
         exit(-1);
 
     //if you use another input size,pleaze change input shape

examples/scrfd.cpp

@@ -228,9 +228,9 @@ static int detect_scrfd(const cv::Mat& bgr, std::vector<FaceObject>& faceobjects
     // model is converted from
     // https://github.com/deepinsight/insightface/tree/master/detection/scrfd
     // the ncnn model https://github.com/nihui/ncnn-assets/tree/master/models
-    if (!scrfd.load_param("scrfd_500m-opt2.param"))
+    if (scrfd.load_param("scrfd_500m-opt2.param"))
         exit(-1);
-    if (!scrfd.load_model("scrfd_500m-opt2.bin"))
+    if (scrfd.load_model("scrfd_500m-opt2.bin"))
         exit(-1);
 
     int width = bgr.cols;

examples/scrfd_crowdhuman.cpp

@@ -229,9 +229,9 @@ static int detect_scrfd(const cv::Mat& bgr, std::vector<FaceObject>& faceobjects
     // but I have one for detecing cat face, you can have a try here:
     // https://drive.google.com/file/d/1JogkKa0f_09HkENbCnXy9hRYxm35wKTn
 
-    if (!scrfd.load_param("scrfd_crowdhuman.param"))
+    if (scrfd.load_param("scrfd_crowdhuman.param"))
         exit(-1);
-    if (!scrfd.load_model("scrfd_crowdhuman.bin"))
+    if (scrfd.load_model("scrfd_crowdhuman.bin"))
         exit(-1);
 
     int width = bgr.cols;

examples/shufflenetv2.cpp

@@ -32,9 +32,9 @@ static int detect_shufflenetv2(const cv::Mat& bgr, std::vector<float>& cls_score
 
     // https://github.com/miaow1988/ShuffleNet_V2_pytorch_caffe
     // models can be downloaded from https://github.com/miaow1988/ShuffleNet_V2_pytorch_caffe/releases
-    if (!shufflenetv2.load_param("shufflenet_v2_x0.5.param"))
+    if (shufflenetv2.load_param("shufflenet_v2_x0.5.param"))
         exit(-1);
-    if (!shufflenetv2.load_model("shufflenet_v2_x0.5.bin"))
+    if (shufflenetv2.load_model("shufflenet_v2_x0.5.bin"))
         exit(-1);
 
     ncnn::Mat in = ncnn::Mat::from_pixels_resize(bgr.data, ncnn::Mat::PIXEL_BGR, bgr.cols, bgr.rows, 224, 224);

examples/simplepose.cpp

@@ -44,9 +44,9 @@ static int detect_posenet(const cv::Mat& bgr, std::vector<KeyPoint>& keypoints)
     //      pose_net.export('pose')
     // then mxnet2ncnn
     // the ncnn model https://github.com/nihui/ncnn-assets/tree/master/models
-    if (!posenet.load_param("pose.param"))
+    if (posenet.load_param("pose.param"))
         exit(-1);
-    if (!posenet.load_model("pose.bin"))
+    if (posenet.load_model("pose.bin"))
         exit(-1);
 
     int w = bgr.cols;

examples/squeezenet.cpp

@@ -31,9 +31,9 @@ static int detect_squeezenet(const cv::Mat& bgr, std::vector<float>& cls_scores)
     squeezenet.opt.use_vulkan_compute = true;
 
     // the ncnn model https://github.com/nihui/ncnn-assets/tree/master/models
-    if (!squeezenet.load_param("squeezenet_v1.1.param"))
+    if (squeezenet.load_param("squeezenet_v1.1.param"))
         exit(-1);
-    if (!squeezenet.load_model("squeezenet_v1.1.bin"))
+    if (squeezenet.load_model("squeezenet_v1.1.bin"))
         exit(-1);
 
     ncnn::Mat in = ncnn::Mat::from_pixels_resize(bgr.data, ncnn::Mat::PIXEL_BGR, bgr.cols, bgr.rows, 227, 227);

examples/squeezenet_c_api.cpp

@@ -34,9 +34,9 @@ static int detect_squeezenet(const cv::Mat& bgr, std::vector<float>& cls_scores)
     ncnn_net_set_option(squeezenet, opt);
 
     // the ncnn model https://github.com/nihui/ncnn-assets/tree/master/models
-    if (!ncnn_net_load_param(squeezenet, "squeezenet_v1.1.param"))
+    if (ncnn_net_load_param(squeezenet, "squeezenet_v1.1.param"))
         exit(-1);
-    if (!ncnn_net_load_model(squeezenet, "squeezenet_v1.1.bin"))
+    if (ncnn_net_load_model(squeezenet, "squeezenet_v1.1.bin"))
         exit(-1);
 
     ncnn_mat_t in = ncnn_mat_from_pixels_resize(bgr.data, NCNN_MAT_PIXEL_BGR, bgr.cols, bgr.rows, bgr.cols * 3, 227, 227, NULL);

examples/squeezenetssd.cpp

@@ -41,9 +41,9 @@ static int detect_squeezenet(const cv::Mat& bgr, std::vector<Object>& objects)
     // squeezenet_ssd_voc_deploy.prototxt
     // https://drive.google.com/open?id=0B3gersZ2cHIxdGpyZlZnbEQ5Snc
     // the ncnn model https://github.com/nihui/ncnn-assets/tree/master/models
-    if (!squeezenet.load_param("squeezenet_ssd_voc.param"))
+    if (squeezenet.load_param("squeezenet_ssd_voc.param"))
         exit(-1);
-    if (!squeezenet.load_model("squeezenet_ssd_voc.bin"))
+    if (squeezenet.load_model("squeezenet_ssd_voc.bin"))
         exit(-1);
 
     const int target_size = 300;

examples/yolact.cpp

@@ -127,9 +127,9 @@ static int detect_yolact(const cv::Mat& bgr, std::vector<Object>& objects)
     // original model converted from https://github.com/dbolya/yolact
     // yolact_resnet50_54_800000.pth
     // the ncnn model https://github.com/nihui/ncnn-assets/tree/master/models
-    if (!yolact.load_param("yolact.param"))
+    if (yolact.load_param("yolact.param"))
         exit(-1);
-    if (!yolact.load_model("yolact.bin"))
+    if (yolact.load_model("yolact.bin"))
         exit(-1);
 
     const int target_size = 550;

examples/yolov2.cpp

@@ -41,9 +41,9 @@ static int detect_yolov2(const cv::Mat& bgr, std::vector<Object>& objects)
     // https://github.com/eric612/MobileNet-YOLO/blob/master/models/yolov2/mobilenet_yolo_deploy.prototxt
     // https://github.com/eric612/MobileNet-YOLO/blob/master/models/yolov2/mobilenet_yolo_deploy_iter_80000.caffemodel
     // the ncnn model https://github.com/nihui/ncnn-assets/tree/master/models
-    if (!yolov2.load_param("mobilenet_yolo.param"))
+    if (yolov2.load_param("mobilenet_yolo.param"))
         exit(-1);
-    if (!yolov2.load_model("mobilenet_yolo.bin"))
+    if (yolov2.load_model("mobilenet_yolo.bin"))
         exit(-1);
 
     const int target_size = 416;

examples/yolov3.cpp

@@ -41,9 +41,9 @@ static int detect_yolov3(const cv::Mat& bgr, std::vector<Object>& objects)
     // param : https://drive.google.com/open?id=1V9oKHP6G6XvXZqhZbzNKL6FI_clRWdC-
     // bin : https://drive.google.com/open?id=1DBcuFCr-856z3FRQznWL_S5h-Aj3RawA
     // the ncnn model https://github.com/nihui/ncnn-assets/tree/master/models
-    if (!yolov3.load_param("mobilenetv2_yolov3.param"))
+    if (yolov3.load_param("mobilenetv2_yolov3.param"))
         exit(-1);
-    if (!yolov3.load_model("mobilenetv2_yolov3.bin"))
+    if (yolov3.load_model("mobilenetv2_yolov3.bin"))
         exit(-1);
 
     const int target_size = 352;

examples/yolov4.cpp

@@ -73,9 +73,9 @@ static int init_yolov4(ncnn::Net* yolov4, int* target_size)
     *target_size = 608;
 #endif
 
-    if (!yolov4->load_param(yolov4_param))
+    if (yolov4->load_param(yolov4_param))
         exit(-1);
-    if (!yolov4->load_model(yolov4_model))
+    if (yolov4->load_model(yolov4_model))
         exit(-1);
 
     return 0;

examples/yolov5.cpp

@@ -276,16 +276,16 @@ static int detect_yolov5(const cv::Mat& bgr, std::vector<Object>& objects)
     // original pretrained model from https://github.com/ultralytics/yolov5
     // the ncnn model https://github.com/nihui/ncnn-assets/tree/master/models
 #if YOLOV5_V60
-    if (!yolov5.load_param("yolov5s_6.0.param"))
+    if (yolov5.load_param("yolov5s_6.0.param"))
         exit(-1);
-    if (!yolov5.load_model("yolov5s_6.0.bin"))
+    if (yolov5.load_model("yolov5s_6.0.bin"))
         exit(-1);
 #else
     yolov5.register_custom_layer("YoloV5Focus", YoloV5Focus_layer_creator);
 
-    if (!yolov5.load_param("yolov5s.param"))
+    if (yolov5.load_param("yolov5s.param"))
         exit(-1);
-    if (!yolov5.load_model("yolov5s.bin"))
+    if (yolov5.load_model("yolov5s.bin"))
         exit(-1);
 #endif
 

examples/yolov5_pnnx.cpp

@@ -207,9 +207,9 @@ static int detect_yolov5(const cv::Mat& bgr, std::vector<Object>& objects)
 
     // original pretrained model from https://github.com/ultralytics/yolov5
     // the ncnn model https://github.com/nihui/ncnn-assets/tree/master/models
-    if (!yolov5.load_param("yolov5s.ncnn.param"))
+    if (yolov5.load_param("yolov5s.ncnn.param"))
         exit(-1);
-    if (!yolov5.load_model("yolov5s.ncnn.bin"))
+    if (yolov5.load_model("yolov5s.ncnn.bin"))
         exit(-1);
 
     const int target_size = 640;

examples/yolox.cpp

@@ -261,9 +261,9 @@ static int detect_yolox(const cv::Mat& bgr, std::vector<Object>& objects)
     // ncnn model param: https://github.com/Megvii-BaseDetection/YOLOX/releases/download/0.1.1rc0/yolox_s_ncnn.tar.gz
     // NOTE that newest version YOLOX remove normalization of model (minus mean and then div by std),
     // which might cause your model outputs becoming a total mess, plz check carefully.
-    if (!yolox.load_param("yolox.param"))
+    if (yolox.load_param("yolox.param"))
         exit(-1);
-    if (!yolox.load_model("yolox.bin"))
+    if (yolox.load_model("yolox.bin"))
         exit(-1);
 
     int img_w = bgr.cols;