Fix evaluation import problem

csrcs/fastdeploy/vision/ppdet/ppyoloe.cc

@@ -130,8 +130,8 @@ bool PPYOLOE::Preprocess(Mat* mat, std::vector<FDTensor>* outputs) {
 
   (*outputs)[1].Allocate({1, 2}, FDDataType::FP32, InputInfoOfRuntime(1).name);
   float* ptr = static_cast<float*>((*outputs)[1].MutableData());
-  ptr[0] = mat->Height() * 1.0 / mat->Height();
-  ptr[1] = mat->Width() * 1.0 / mat->Width();
+  ptr[0] = mat->Height() * 1.0 / origin_h;
+  ptr[1] = mat->Width() * 1.0 / origin_w;
   return true;
 }
 

fastdeploy/vision/evaluation/utils/__init__.py

@@ -19,4 +19,3 @@
 from .map_utils import *
 from .coco_utils import *
 from .coco import *
-from .cityscapes import Cityscapes

fastdeploy/vision/evaluation/utils/coco.py

@@ -15,7 +15,6 @@
 from __future__ import absolute_import
 import copy
 import os.path as osp
-import six
 import sys
 import numpy as np
 from . import fd_logging as logging

fastdeploy/vision/evaluation/utils/coco_utils.py

@@ -18,10 +18,9 @@
 
 import sys
 import numpy as np
-import itertools
 from .map_utils import draw_pr_curve
 from .json_results import get_det_res, get_det_poly_res, get_seg_res, get_solov2_segm_res
-import logging as logging
+from . import fd_logging as logging
 import copy
 
 
@@ -202,6 +201,8 @@ def cocoapi_eval(anns,
                 file_name='{}_precision_recall_curve.jpg'.format(nm["name"]))
 
         num_columns = min(6, len(results_per_category) * 2)
+
+        import itertools
         results_flatten = list(itertools.chain(*results_per_category))
         headers = ['category', 'AP'] * (num_columns // 2)
         results_2d = itertools.zip_longest(

model_zoo/vision/yolov7/README.md

@@ -26,9 +26,12 @@
   #下载yolov7模型文件
   wget https://github.com/WongKinYiu/yolov7/releases/download/v0.1/yolov7.pt
 
-  # 导出onnx格式文件
+  # 导出onnx格式文件 (Tips: 对应 YOLOv7 release v0.1 代码)
   python models/export.py --grid --dynamic --weights PATH/TO/yolov7.pt
 
+  # 如果您的代码版本中有支持NMS的ONNX文件导出，请使用如下命令导出ONNX文件(请暂时不要使用 "--end2end"，我们后续将支持带有NMS的ONNX模型的部署)
+  python export.py --grid --dynamic --weights PATH/TO/yolov7.pt
+
   # 移动onnx文件到demo目录
   cp PATH/TO/yolov7.onnx PATH/TO/model_zoo/vision/yolov7/
   ```

model_zoo/vision/yolov7/cpp/README.md

@@ -12,9 +12,11 @@
   #下载yolov7模型文件
   wget https://github.com/WongKinYiu/yolov7/releases/download/v0.1/yolov7.pt
 
-  # 导出onnx格式文件
+  # 导出onnx格式文件 (Tips: 对应 YOLOv7 release v0.1 代码)
   python models/export.py --grid --dynamic --weights PATH/TO/yolov7.pt
 
+  # 如果您的代码版本中有支持NMS的ONNX文件导出，请使用如下命令导出ONNX文件(请暂时不要使用 "--end2end"，我们后续将支持带有NMS的ONNX模型的部署)
+  python export.py --grid --dynamic --weights PATH/TO/yolov7.pt
   ```
 
 

requirements.txt

@@ -1,2 +1,5 @@
 opencv-python
 tqdm
+numpy
+pycocotools
+colorama

setup.py

@@ -52,6 +52,8 @@
 setup_configs["TRT_DIRECTORY"] = os.getenv("TRT_DIRECTORY", "UNDEFINED")
 setup_configs["CUDA_DIRECTORY"] = os.getenv("CUDA_DIRECTORY",
                                             "/usr/local/cuda")
+if os.getenv("CMAKE_CXX_COMPILER", None) is not None:
+    setup_configs["CMAKE_CXX_COMPILER"] = os.getenv("CMAKE_CXX_COMPILER")
 
 TOP_DIR = os.path.realpath(os.path.dirname(__file__))
 SRC_DIR = os.path.join(TOP_DIR, "fastdeploy")