███ $ python solution.py -l

...

Solutions name:

mask_det_yolo3

…

hand_det_yolox

hand_tracking_yolox

single_hand_pose_yolox_mbv2

multi_hand_pose_yolox_mbv2

███ $ python solution.py -s hand_det_yolox

...

███/modelbox$ python create.py -t server -n garbage_det -s hand_det_yolox

sdk version is modelbox-xxx

success: create garbage_det in ███/modelbox/workspace
workspace目录下将创建出garbage_det工程，工程内容如下所示：


garbage_det

|--bin

│  |--main.bat：应用执行入口

│  |--mock_task.toml：应用在本地执行时的输入输出配置，此应用默认使用本地视频文件为输入源，最终结果输出到另一本地视频文件，可根据需要修改

|--CMake：存放一些自定义CMake函数

|--data：存放应用运行所需要的图片、视频、文本、配置等数据

│  |--hand.mp4：手部检测测试用视频文件—>替换为自己的视频

|--dependence

│  |--modelbox_requirements.txt：应用运行依赖的外部库在此文件定义

|--etc

│  |--flowunit：应用所需的功能单元存放在此目录

│  │  |--cpp：存放C++功能单元编译后的动态链接库，此应用没有C++功能单元

│  │  |--yolox_post：手部检测使用的是YOLOX模型，此处即为后处理功能单元（修改toml文件的类别参数和py文件的draw函数）

|--flowunit_cpp：存放C++功能单元的源代码，此应用没有C++功能单元

|--graph：存放流程图

│  |--garbage_det.toml：默认流程图，使用本地视频文件作为输入源

│  |--garbage_det_camera.toml：摄像头输入对应的流程图

│  |--modelbox.conf：modelbox相关配置

|--hilens_data_dir：存放应用输出的结果文件、日志、性能统计信息

|--model：推理功能单元目录

│  |--detect_hand：手部检测推理功能单元

│  │  |--detect_hand.toml：手部检测推理功能单元的配置文件

│  │  |--yolox_hand.onnx：手部检测onnx模型—>更改为自己的模型

|--build_project.sh：应用构建脚本

|--CMakeLists.txt

|--rpm：打包rpm时生成的目录，将存放rpm包所需数据

|--rpm_copyothers.sh：rpm打包时的辅助脚本

def draw(self, img, bboxes):

        h, w, c = img.shape

        thickness = 2

        font_scale = 1

        text_font = cv2.FONT_HERSHEY_SIMPLEX

        clss_to_text = {

        0: "Disposable snack box",

        1: "Books and papers",

        2: "Power bank",

        3: "Leftovers",

        4: "Package",

        5: "Trash can",

        6: "Plastic utensils",

        7: "Plastic toys",

        8: "Plastic coat hanger",

        9: "Big Bones",

        10: "Dry battery",

        11: "Express paper bag",

        12: "Plug wire",

        13: "Old clothes",

        14: "The can",

        15: "Pillow",

        16: "Skin and pulp",

        17: "Stuffed animal",

        18: "Defacing plastic",

        19: "Soiled paper",

        20: "Toiletries",

        21: "Cigarette butts",

        22: "Toothpick",

        23: "Glassware",

        24: "Block",

        25: "Chopsticks",

        26: "Carton carton",

        27: "Pot",

        27: "Tea residue",

        29: "Vegetable help vegetable leaf",

        30: "Shell",

        31: "The spice bottle",

        32: "Paste",

        33: "Expired drugs",

        34: "Bottle",

        35: "Metal kitchenware",

        36: "Metal ware",

        37: "Metal food cans",

        38: "Pot",

        39: "Ceramic vessels",

        40: "Shoes",

        41: "Edible oil drum",

        42: "Beverage bottle",

        43: "Bones"

        }

        for box in bboxes:

            x1, y1, x2, y2, score, clss = box

            cv2.putText(img, clss_to_text[int(clss)]+': '+"{:.3}".format(score*100)+'%', (int(x1 * w)+10, int(y1 * h)+30),text_font, font_scale, (0, int(clss+1)*5, 0), thickness)

            cv2.rectangle(img, (int(x1 * w), int(y1 * h)), (int(x2 * w), int(y2 * h)), (0, int(clss+1)*5, 0), 3)

[input]

type = "url"

url = "../data/garbage.mp4"

[output]

type = “local”

url = “…/hilens_data_dir/garbage_detection_result.mp4”

███$ ./build_project.sh

dos2unix: converting file xxx.toml to Unix format...

...

build success: you can run main.bat in ./bin folder

Press ‘p’ to pause…, any key to exit
然后执行bin/main.bat运行应用：

███$ ./bin/main.bat

…

[input]

type = "url"

url = "0"  # 表示0号摄像头，即PC自带摄像头，若PC无摄像头需外接USB摄像头

[output]

type = “local”

url = “0:garbage_det” # 表示名为garbage_det的本地窗口

python ./create.py -t rpm -n garbage_det

sdk version is modelbox-win10-x64-1.1.0.5

call mb-pkg-tool pack [folder] > [rpm file] to building rpm, waiting...

success: create garbage_det.rpm in D:\modelbox-win10-x64-1.1.0.5/workspace/garbage_det