ADD file via upload

KeyPressMoudle.py

@@ -1,18 +1,18 @@
-import pygame
+import pygame
-
+
-def init():
+def init():
-    pygame.init()
+    pygame.init()
-    win = pygame.display.set_mode((400, 400))
+    win = pygame.display.set_mode((400, 400))
-
+
-def getKey(keyName):
+def getKey(keyName):
-    ans = False
+    ans = False
-    for eve in pygame.event.get(): pass
+    for eve in pygame.event.get(): pass
-    keyInput = pygame.key.get_pressed()
+    keyInput = pygame.key.get_pressed()
-    myKey = getattr(pygame,'K_{}'.format(keyName))
+    myKey = getattr(pygame,'K_{}'.format(keyName))
-    if keyInput[myKey]:
+    if keyInput[myKey]:
-        ans = True
+        ans = True
-    pygame.display.update()
+    pygame.display.update()
-    return ans
+    return ans
-
+
-if __name__ == '__main__':
+if __name__ == '__main__':
     init()

main.py

@@ -0,0 +1,87 @@
+# This is a sample Python script.
+
+# Press Shift+F10 to execute it or replace it with your code.
+# Press Double Shift to search everywhere for classes, files, tool windows, actions, and settings.
+
+
+import logging
+import time
+import cv2
+from djitellopy import tello
+import KeyPressMoudle as kp  # 用于获取键盘按键
+from time import sleep
+
+def getKeyboardInput(drone, speed, image):
+    lr, fb, ud, yv = 0, 0, 0, 0
+    key_pressed = 0
+    if kp.getKey("e"):
+        cv2.imwrite('D:/snap-{}.jpg'.format(time.strftime("%H%M%S", time.localtime())), image)
+    if kp.getKey("UP"):
+        Drone.takeoff()
+    elif kp.getKey("DOWN"):
+        Drone.land()
+
+    if kp.getKey("j"):
+        key_pressed = 1
+        lr = -speed
+    elif kp.getKey("l"):
+        key_pressed = 1
+        lr = speed
+
+    if kp.getKey("i"):
+        key_pressed = 1
+        fb = speed
+    elif kp.getKey("k"):
+        key_pressed = 1
+        fb = -speed
+
+    if kp.getKey("w"):
+        key_pressed = 1
+        ud = speed
+    elif kp.getKey("s"):
+        key_pressed = 1
+        ud = -speed
+
+    if kp.getKey("a"):
+        key_pressed = 1
+        yv = -speed
+    elif kp.getKey("d"):
+        key_pressed = 1
+        yv = speed
+    InfoText = "battery : {0}% height: {1}cm   time: {2}".format(drone.get_battery(), drone.get_height(), time.strftime("%H:%M:%S",time.localtime()))
+    cv2.putText(image, InfoText, (10, 20), font, fontScale, (0, 0, 255), lineThickness)
+    if key_pressed == 1:
+        InfoText = "Command : lr:{0}% fb:{1} ud:{2} yv:{3}".format(lr, fb, ud, yv)
+        cv2.putText(image, InfoText, (10, 40), font, fontScale, (0, 0, 255), lineThickness)
+
+    drone.send_rc_control(lr, fb, ud, yv)
+
+# 主程序
+# 摄像头设置
+Camera_Width = 720
+Camera_Height = 480
+DetectRange = [6000, 11000]  # DetectRange[0] 是保持静止的检测人脸面积阈值下限，DetectRange[0] 是保持静止的检测人脸面积阈值上限
+PID_Parameter = [0.5, 0.0004, 0.4]
+pErrorRotate, pErrorUp = 0, 0
+
+# 字体设置
+font = cv2.FONT_HERSHEY_SIMPLEX
+fontScale = 0.5
+fontColor = (255, 0, 0)
+lineThickness = 1
+
+# Tello初始化设置
+Drone = tello.Tello()  # 创建飞行器对象
+Drone.connect()  # 连接到飞行器
+Drone.streamon()  # 开启视频传输
+Drone.LOGGER.setLevel(logging.ERROR)  # 只显示错误信息
+sleep(5)  #  等待视频初始化
+kp.init()  # 初始化按键处理模块
+
+
+while True:
+    OriginalImage = Drone.get_frame_read().frame
+    Image = cv2.resize(OriginalImage, (Camera_Width, Camera_Height))
+    getKeyboardInput(drone=Drone, speed=70, image=Image)  # 按键控制
+    cv2.imshow("Drone Control Centre", Image)
+    cv2.waitKey(1)

src/PaddleClas/MANIFEST.in

@@ -1,7 +0,0 @@
-include LICENSE.txt
-include README.md
-include docs/en/whl_en.md
-recursive-include deploy/python predict_cls.py preprocess.py postprocess.py det_preprocess.py
-recursive-include deploy/utils get_image_list.py config.py logger.py predictor.py
-
-recursive-include ppcls/ *.py *.txt

src/PaddleClas/__init__.py

@@ -1,17 +0,0 @@
-# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
-#
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at
-#
-#     http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-
-__all__ = ['PaddleClas']
-from .paddleclas import PaddleClas
-from ppcls.arch.backbone import *

src/PaddleClas/benchmark/README.md

@@ -1,27 +0,0 @@
-# benchmark使用说明
-
-此目录所有shell脚本是为了测试PaddleClas中不同模型的速度指标，如单卡训练速度指标、多卡训练速度指标等。
-
-## 相关脚本说明
-
-一共有3个脚本：
-
-- `prepare_data.sh`: 下载相应的测试数据，并配置好数据路径
-- `run_benchmark.sh`: 执行单独一个训练测试的脚本，具体调用方式，可查看脚本注释
-- `run_all.sh`: 执行所有训练测试的入口脚本
-
-## 使用说明
-
-**注意**：为了跟PaddleClas中其他的模块的执行目录保持一致，此模块的执行目录为`PaddleClas`的根目录。
-
-### 1.准备数据
-
-```shell
-bash benchmark/prepare_data.sh
-```
-
-### 2.执行所有模型的测试
-
-```shell
-bash benchmark/run_all.sh
-```

src/PaddleClas/benchmark/prepare_data.sh

@@ -1,22 +0,0 @@
-#!/bin/bash
-dataset_url=$1
-
-package_check_list=(imageio tqdm Cython pycocotools tb_paddle scipy pandas wget h5py sklearn opencv-python visualdl)
-for package in ${package_check_list[@]}; do
-    if python -c "import ${package}" >/dev/null 2>&1; then
-        echo "${package} have already installed"
-    else
-        echo "${package} NOT FOUND"
-        pip install ${package}
-        echo "${package} installed"
-    fi
-done
-
-cd dataset
-rm -rf ILSVRC2012
-wget -nc ${dataset_url}
-tar xf ILSVRC2012_val.tar
-ln -s ILSVRC2012_val ILSVRC2012
-cd ILSVRC2012
-ln -s val_list.txt train_list.txt
-cd ../../

src/PaddleClas/benchmark/run_all.sh

@@ -1,31 +0,0 @@
-# 提供可稳定复现性能的脚本，默认在标准docker环境内py37执行： paddlepaddle/paddle:latest-gpu-cuda10.1-cudnn7  paddle=2.1.2  py=37
-# 执行目录：需说明
-# cd **
-# 1 安装该模型需要的依赖 (如需开启优化策略请注明)
-# pip install ...
-# 2 拷贝该模型需要数据、预训练模型
-# 3 批量运行（如不方便批量，1，2需放到单个模型中）
-log_path=${LOG_PATH_INDEX_DIR:-$(pwd)}  # LOG_PATH_INDEX_DIR 后续QA设置参数
-model_mode_list=(MobileNetV1 MobileNetV2 MobileNetV3_large_x1_0 ShuffleNetV2_x1_0 HRNet_W48_C SwinTransformer_tiny_patch4_window7_224 alt_gvt_base)    # benchmark 监控模型列表
-#model_mode_list=(MobileNetV1 MobileNetV2 MobileNetV3_large_x1_0 EfficientNetB0 ShuffleNetV2_x1_0 DenseNet121 HRNet_W48_C SwinTransformer_tiny_patch4_window7_224 alt_gvt_base)   # 该脚本支持列表
-fp_item_list=(fp32)
-#bs_list=(32 64 96 128)
-for model_mode in ${model_mode_list[@]}; do
-      for fp_item in ${fp_item_list[@]}; do
-          if [ ${model_mode} = MobileNetV3_large_x1_0 ] || [ ${model_mode} = ShuffleNetV2_x1_0 ]; then
-              bs_list=(256)
-          else
-              bs_list=(64)
-          fi
-          for bs_item in ${bs_list[@]};do
-	    echo "index is speed, 1gpus, begin, ${model_name}"
-	    run_mode=sp
-	    CUDA_VISIBLE_DEVICES=0 bash benchmark/run_benchmark.sh ${run_mode} ${bs_item} ${fp_item} 1 ${model_mode} | tee ${log_path}/clas_${model_mode}_${run_mode}_bs${bs_item}_${fp_item}_1gpus 2>&1    #  (5min)
-	    sleep 10
-            echo "index is speed, 8gpus, run_mode is multi_process, begin, ${model_name}"
-            run_mode=mp
-            CUDA_VISIBLE_DEVICES=0,1,2,3,4,5,6,7 bash benchmark/run_benchmark.sh ${run_mode} ${bs_item} ${fp_item} 1 ${model_mode}| tee ${log_path}/clas_${model_mode}_${run_mode}_bs${bs_item}_${fp_item}_8gpus8p 2>&1
-            sleep 10
-            done
-      done
-done

src/PaddleClas/benchmark/run_benchmark.sh

@@ -1,68 +0,0 @@
-#!/usr/bin/env bash
-set -xe
-# 运行示例：CUDA_VISIBLE_DEVICES=0 bash run_benchmark.sh ${run_mode} ${bs_item} ${fp_item} 500 ${model_mode}
-# 参数说明
-function _set_params(){
-    run_mode=${1:-"sp"}          # 单卡sp|多卡mp
-    batch_size=${2:-"64"}
-    fp_item=${3:-"fp32"}        # fp32|fp16
-    epochs=${4:-"2"}       # 可选，如果需要修改代码提前中断
-    model_item=${5:-"model_item"}
-    run_log_path=${TRAIN_LOG_DIR:-$(pwd)}  # TRAIN_LOG_DIR 后续QA设置该参数
-
-    index=1
-    mission_name="图像分类"           # 模型所属任务名称，具体可参考scripts/config.ini                                （必填）
-    direction_id=0                    # 任务所属方向，0：CV，1：NLP，2：Rec。                                          (必填)
-    skip_steps=8                      # 解析日志，有些模型前几个step耗时长，需要跳过                                  (必填)
-    keyword="ips:"              # 解析日志，筛选出数据所在行的关键字                                            (必填)
-    keyword_loss="loss:"       #选填
-    model_mode=-1                      # 解析日志，具体参考scripts/analysis.py.                                        (必填)
-    ips_unit="images/s"
-    base_batch_size=$batch_size
-#   以下不用修改   
-    device=${CUDA_VISIBLE_DEVICES//,/ }
-    arr=(${device})
-    num_gpu_devices=${#arr[*]}
-    log_file=${run_log_path}/clas_${model_item}_${run_mode}_bs${batch_size}_${fp_item}_${num_gpu_devices}
-    model_name=${model_item}_bs${batch_size}_${fp_item}    # model_item 用于yml匹配，model_name用于入库
-}
-function _train(){
-    echo "Train on ${num_gpu_devices} GPUs"
-    echo "current CUDA_VISIBLE_DEVICES=$CUDA_VISIBLE_DEVICES, gpus=$num_gpu_devices, batch_size=$batch_size"
-
-    if [ ${fp_item} = "fp32" ];then
-        model_config=`find ppcls/configs/ImageNet -name ${model_item}.yaml`
-    else
-        model_config=`find ppcls/configs/ImageNet -name ${model_item}_fp16.yaml`
-    fi
-
-    train_cmd="-c ${model_config} -o DataLoader.Train.sampler.batch_size=${batch_size} -o Global.epochs=${epochs}  -o Global.eval_during_train=False -o Global.print_batch_step=2"
-    case ${run_mode} in
-    sp) train_cmd="python -u tools/train.py ${train_cmd}" ;;
-    mp)
-        train_cmd="python -m paddle.distributed.launch --log_dir=./mylog --gpus=$CUDA_VISIBLE_DEVICES tools/train.py ${train_cmd}"
-        log_parse_file="mylog/workerlog.0" ;;
-    *) echo "choose run_mode(sp or mp)"; exit 1;
-    esac
-    rm -rf mylog
-# 以下不用修改
-    timeout 5m ${train_cmd} > ${log_file} 2>&1
-    if [ $? -ne 0 ];then
-        echo -e "${model_name}, FAIL"
-        export job_fail_flag=1
-    else
-        echo -e "${model_name}, SUCCESS"
-        export job_fail_flag=0
-    fi
-    kill -9 `ps -ef|grep 'python'|awk '{print $2}'`
- 
-    if [ $run_mode = "mp" -a -d mylog ]; then
-        rm ${log_file}
-        cp mylog/workerlog.0 ${log_file}
-    fi
-}
-
-source ${BENCHMARK_ROOT}/scripts/run_model.sh # 在该脚本中会对符合benchmark规范的log使用analysis.py 脚本进行性能数据解析;该脚本在连调时可从benchmark repo中下载https://github.com/PaddlePaddle/benchmark/blob/master/scripts/run_model.sh;如果不联调只想要产出训练log可以注掉本行,提交时需打开
-_set_params $@
-_run
-#_train

src/PaddleClas/deploy/.idea/.gitignore

@@ -1,3 +0,0 @@
-# 默认忽略的文件
-/shelf/
-/workspace.xml

src/PaddleClas/deploy/.idea/deploy.iml

@@ -1,12 +0,0 @@
-<?xml version="1.0" encoding="UTF-8"?>
-<module type="PYTHON_MODULE" version="4">
-  <component name="NewModuleRootManager">
-    <content url="file://$MODULE_DIR$" />
-    <orderEntry type="inheritedJdk" />
-    <orderEntry type="sourceFolder" forTests="false" />
-  </component>
-  <component name="PyDocumentationSettings">
-    <option name="format" value="GOOGLE" />
-    <option name="myDocStringFormat" value="Google" />
-  </component>
-</module>

src/PaddleClas/deploy/.idea/inspectionProfiles/profiles_settings.xml

@@ -1,6 +0,0 @@
-<component name="InspectionProjectProfileManager">
-  <settings>
-    <option name="USE_PROJECT_PROFILE" value="false" />
-    <version value="1.0" />
-  </settings>
-</component>

src/PaddleClas/deploy/.idea/misc.xml

@@ -1,4 +0,0 @@
-<?xml version="1.0" encoding="UTF-8"?>
-<project version="4">
-  <component name="ProjectRootManager" version="2" project-jdk-name="Python 3.9" project-jdk-type="Python SDK" />
-</project>

src/PaddleClas/deploy/.idea/modules.xml

@@ -1,8 +0,0 @@
-<?xml version="1.0" encoding="UTF-8"?>
-<project version="4">
-  <component name="ProjectModuleManager">
-    <modules>
-      <module fileurl="file://$PROJECT_DIR$/.idea/deploy.iml" filepath="$PROJECT_DIR$/.idea/deploy.iml" />
-    </modules>
-  </component>
-</project>

src/PaddleClas/deploy/.scannerwork/report-task.txt

@@ -1,6 +0,0 @@
-projectKey=deploy
-serverUrl=http://localhost:9000
-serverVersion=8.1.0.31237
-dashboardUrl=http://localhost:9000/dashboard?id=deploy
-ceTaskId=AYA_xvBwrgFtfprwzYuQ
-ceTaskUrl=http://localhost:9000/api/ce/task?id=AYA_xvBwrgFtfprwzYuQ