├── .gitignore ├── LICENSE ├── README.md ├── func.py ├── main.py ├── performance.sh ├── rkcat.sh ├── rknnModel └── yolov5s_relu_tk2_RK3588_i8.rknn └── rknnpool.py /.gitignore: -------------------------------------------------------------------------------- 1 | # Byte-compiled / optimized / DLL files 2 | __pycache__/ 3 | *.py[cod] 4 | *$py.class 5 | 6 | # C extensions 7 | *.so 8 | 9 | # Distribution / packaging 10 | .Python 11 | build/ 12 | develop-eggs/ 13 | dist/ 14 | downloads/ 15 | eggs/ 16 | .eggs/ 17 | lib/ 18 | lib64/ 19 | parts/ 20 | sdist/ 21 | var/ 22 | wheels/ 23 | share/python-wheels/ 24 | *.egg-info/ 25 | .installed.cfg 26 | *.egg 27 | MANIFEST 28 | 29 | # PyInstaller 30 | # Usually these files are written by a python script from a template 31 | # before PyInstaller builds the exe, so as to inject date/other infos into it. 32 | *.manifest 33 | *.spec 34 | 35 | # Installer logs 36 | pip-log.txt 37 | pip-delete-this-directory.txt 38 | 39 | # Unit test / coverage reports 40 | htmlcov/ 41 | .tox/ 42 | .nox/ 43 | .coverage 44 | .coverage.* 45 | .cache 46 | nosetests.xml 47 | coverage.xml 48 | *.cover 49 | *.py,cover 50 | .hypothesis/ 51 | .pytest_cache/ 52 | cover/ 53 | 54 | # Translations 55 | *.mo 56 | *.pot 57 | 58 | # Django stuff: 59 | *.log 60 | local_settings.py 61 | db.sqlite3 62 | db.sqlite3-journal 63 | 64 | # Flask stuff: 65 | instance/ 66 | .webassets-cache 67 | 68 | # Scrapy stuff: 69 | .scrapy 70 | 71 | # Sphinx documentation 72 | docs/_build/ 73 | 74 | # PyBuilder 75 | .pybuilder/ 76 | target/ 77 | 78 | # Jupyter Notebook 79 | .ipynb_checkpoints 80 | 81 | # IPython 82 | profile_default/ 83 | ipython_config.py 84 | 85 | # pyenv 86 | # For a library or package, you might want to ignore these files since the code is 87 | # intended to run in multiple environments; otherwise, check them in: 88 | # .python-version 89 | 90 | # pipenv 91 | # According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control. 92 | # However, in case of collaboration, if having platform-specific dependencies or dependencies 93 | # having no cross-platform support, pipenv may install dependencies that don't work, or not 94 | # install all needed dependencies. 95 | #Pipfile.lock 96 | 97 | # poetry 98 | # Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control. 99 | # This is especially recommended for binary packages to ensure reproducibility, and is more 100 | # commonly ignored for libraries. 101 | # https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control 102 | #poetry.lock 103 | 104 | # pdm 105 | # Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control. 106 | #pdm.lock 107 | # pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it 108 | # in version control. 109 | # https://pdm.fming.dev/#use-with-ide 110 | .pdm.toml 111 | 112 | # PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm 113 | __pypackages__/ 114 | 115 | # Celery stuff 116 | celerybeat-schedule 117 | celerybeat.pid 118 | 119 | # SageMath parsed files 120 | *.sage.py 121 | 122 | # Environments 123 | .env 124 | .venv 125 | env/ 126 | venv/ 127 | ENV/ 128 | env.bak/ 129 | venv.bak/ 130 | 131 | # Spyder project settings 132 | .spyderproject 133 | .spyproject 134 | 135 | # Rope project settings 136 | .ropeproject 137 | 138 | # mkdocs documentation 139 | /site 140 | 141 | # mypy 142 | .mypy_cache/ 143 | .dmypy.json 144 | dmypy.json 145 | 146 | # Pyre type checker 147 | .pyre/ 148 | 149 | # pytype static type analyzer 150 | .pytype/ 151 | 152 | # Cython debug symbols 153 | cython_debug/ 154 | 155 | # PyCharm 156 | # JetBrains specific template is maintained in a separate JetBrains.gitignore that can 157 | # be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore 158 | # and can be added to the global gitignore or merged into this file. 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x[:, 2] / 2 # top left x 25 | y[:, 1] = x[:, 1] - x[:, 3] / 2 # top left y 26 | y[:, 2] = x[:, 0] + x[:, 2] / 2 # bottom right x 27 | y[:, 3] = x[:, 1] + x[:, 3] / 2 # bottom right y 28 | return y 29 | 30 | 31 | def process(input, mask, anchors): 32 | 33 | anchors = [anchors[i] for i in mask] 34 | grid_h, grid_w = map(int, input.shape[0:2]) 35 | 36 | box_confidence = input[..., 4] 37 | box_confidence = np.expand_dims(box_confidence, axis=-1) 38 | 39 | box_class_probs = input[..., 5:] 40 | 41 | box_xy = input[..., :2] *2 - 0.5 42 | 43 | col = np.tile(np.arange(0, grid_w), grid_w).reshape(-1, grid_w) 44 | row = np.tile(np.arange(0, grid_h).reshape(-1, 1), grid_h) 45 | col = col.reshape(grid_h, grid_w, 1, 1).repeat(3, axis=-2) 46 | row = row.reshape(grid_h, grid_w, 1, 1).repeat(3, axis=-2) 47 | grid = np.concatenate((col, row), axis=-1) 48 | box_xy += grid 49 | box_xy *= int(IMG_SIZE/grid_h) 50 | 51 | box_wh = pow(input[..., 2:4] *2, 2) 52 | box_wh = box_wh * anchors 53 | 54 | return np.concatenate((box_xy, box_wh), axis=-1), box_confidence, box_class_probs 55 | 56 | 57 | def filter_boxes(boxes, box_confidences, box_class_probs): 58 | """Filter boxes with box threshold. It's a bit different with origin yolov5 post process! 59 | 60 | # Arguments 61 | boxes: ndarray, boxes of objects. 62 | box_confidences: ndarray, confidences of objects. 63 | box_class_probs: ndarray, class_probs of objects. 64 | 65 | # Returns 66 | boxes: ndarray, filtered boxes. 67 | classes: ndarray, classes for boxes. 68 | scores: ndarray, scores for boxes. 69 | """ 70 | boxes = boxes.reshape(-1, 4) 71 | box_confidences = box_confidences.reshape(-1) 72 | box_class_probs = box_class_probs.reshape(-1, box_class_probs.shape[-1]) 73 | 74 | _box_pos = np.where(box_confidences >= OBJ_THRESH) 75 | boxes = boxes[_box_pos] 76 | box_confidences = box_confidences[_box_pos] 77 | box_class_probs = box_class_probs[_box_pos] 78 | 79 | class_max_score = np.max(box_class_probs, axis=-1) 80 | classes = np.argmax(box_class_probs, axis=-1) 81 | _class_pos = np.where(class_max_score >= OBJ_THRESH) 82 | 83 | return boxes[_class_pos], classes[_class_pos], (class_max_score * box_confidences)[_class_pos] 84 | 85 | 86 | def nms_boxes(boxes, scores): 87 | """Suppress non-maximal boxes. 88 | 89 | # Arguments 90 | boxes: ndarray, boxes of objects. 91 | scores: ndarray, scores of objects. 92 | 93 | # Returns 94 | keep: ndarray, index of effective boxes. 95 | """ 96 | x = boxes[:, 0] 97 | y = boxes[:, 1] 98 | w = boxes[:, 2] - boxes[:, 0] 99 | h = boxes[:, 3] - boxes[:, 1] 100 | 101 | areas = w * h 102 | order = scores.argsort()[::-1] 103 | 104 | keep = [] 105 | while order.size > 0: 106 | i = order[0] 107 | keep.append(i) 108 | 109 | xx1 = np.maximum(x[i], x[order[1:]]) 110 | yy1 = np.maximum(y[i], y[order[1:]]) 111 | xx2 = np.minimum(x[i] + w[i], x[order[1:]] + w[order[1:]]) 112 | yy2 = np.minimum(y[i] + h[i], y[order[1:]] + h[order[1:]]) 113 | 114 | w1 = np.maximum(0.0, xx2 - xx1 + 0.00001) 115 | h1 = np.maximum(0.0, yy2 - yy1 + 0.00001) 116 | inter = w1 * h1 117 | 118 | ovr = inter / (areas[i] + areas[order[1:]] - inter) 119 | inds = np.where(ovr <= NMS_THRESH)[0] 120 | order = order[inds + 1] 121 | return np.array(keep) 122 | 123 | 124 | def yolov5_post_process(input_data): 125 | masks = [[0, 1, 2], [3, 4, 5], [6, 7, 8]] 126 | anchors = [[10, 13], [16, 30], [33, 23], [30, 61], [62, 45], 127 | [59, 119], [116, 90], [156, 198], [373, 326]] 128 | 129 | boxes, classes, scores = [], [], [] 130 | for input, mask in zip(input_data, masks): 131 | b, c, s = process(input, mask, anchors) 132 | b, c, s = filter_boxes(b, c, s) 133 | boxes.append(b) 134 | classes.append(c) 135 | scores.append(s) 136 | 137 | boxes = np.concatenate(boxes) 138 | boxes = xywh2xyxy(boxes) 139 | classes = np.concatenate(classes) 140 | scores = np.concatenate(scores) 141 | 142 | nboxes, nclasses, nscores = [], [], [] 143 | for c in set(classes): 144 | inds = np.where(classes == c) 145 | b = boxes[inds] 146 | c = classes[inds] 147 | s = scores[inds] 148 | 149 | keep = nms_boxes(b, s) 150 | 151 | nboxes.append(b[keep]) 152 | nclasses.append(c[keep]) 153 | nscores.append(s[keep]) 154 | 155 | if not nclasses and not nscores: 156 | return None, None, None 157 | 158 | return np.concatenate(nboxes), np.concatenate(nclasses), np.concatenate(nscores) 159 | 160 | 161 | def draw(image, boxes, scores, classes): 162 | for box, score, cl in zip(boxes, scores, classes): 163 | top, left, right, bottom = box 164 | # print('class: {}, score: {}'.format(CLASSES[cl], score)) 165 | # print('box coordinate left,top,right,down: [{}, {}, {}, {}]'.format(top, left, right, bottom)) 166 | top = int(top) 167 | left = int(left) 168 | 169 | cv2.rectangle(image, (top, left), (int(right), int(bottom)), (255, 0, 0), 2) 170 | cv2.putText(image, '{0} {1:.2f}'.format(CLASSES[cl], score), 171 | (top, left - 6), 172 | cv2.FONT_HERSHEY_SIMPLEX, 173 | 0.6, (0, 0, 255), 2) 174 | 175 | def letterbox(im, new_shape=(640, 640), color=(0, 0, 0)): 176 | shape = im.shape[:2] # current shape [height, width] 177 | if isinstance(new_shape, int): 178 | new_shape = (new_shape, new_shape) 179 | 180 | r = min(new_shape[0] / shape[0], new_shape[1] / shape[1]) 181 | 182 | ratio = r, r # width, height ratios 183 | new_unpad = int(round(shape[1] * r)), int(round(shape[0] * r)) 184 | dw, dh = new_shape[1] - new_unpad[0], new_shape[0] - \ 185 | new_unpad[1] # wh padding 186 | 187 | dw /= 2 # divide padding into 2 sides 188 | dh /= 2 189 | 190 | if shape[::-1] != new_unpad: # resize 191 | im = cv2.resize(im, new_unpad, interpolation=cv2.INTER_LINEAR) 192 | top, bottom = int(round(dh - 0.1)), int(round(dh + 0.1)) 193 | left, right = int(round(dw - 0.1)), int(round(dw + 0.1)) 194 | im = cv2.copyMakeBorder(im, top, bottom, left, right, 195 | cv2.BORDER_CONSTANT, value=color) # add border 196 | return im 197 | # return im, ratio, (dw, dh) 198 | 199 | def myFunc(rknn_lite, IMG): 200 | IMG = cv2.cvtColor(IMG, cv2.COLOR_BGR2RGB) 201 | # 等比例缩放 202 | # IMG = letterbox(IMG) 203 | # 强制放缩 204 | IMG = cv2.resize(IMG, (IMG_SIZE, IMG_SIZE)) 205 | outputs = rknn_lite.inference(inputs=[IMG]) 206 | 207 | input0_data = outputs[0].reshape([3, -1]+list(outputs[0].shape[-2:])) 208 | input1_data = outputs[1].reshape([3, -1]+list(outputs[1].shape[-2:])) 209 | input2_data = outputs[2].reshape([3, -1]+list(outputs[2].shape[-2:])) 210 | 211 | input_data = list() 212 | input_data.append(np.transpose(input0_data, (2, 3, 0, 1))) 213 | input_data.append(np.transpose(input1_data, (2, 3, 0, 1))) 214 | input_data.append(np.transpose(input2_data, (2, 3, 0, 1))) 215 | 216 | boxes, classes, scores = yolov5_post_process(input_data) 217 | 218 | IMG = cv2.cvtColor(IMG, cv2.COLOR_RGB2BGR) 219 | if boxes is not None: 220 | draw(IMG, boxes, scores, classes) 221 | return IMG 222 | -------------------------------------------------------------------------------- /main.py: -------------------------------------------------------------------------------- 1 | import cv2 2 | import time 3 | from rknnpool import rknnPoolExecutor 4 | # 图像处理函数，实际应用过程中需要自行修改 5 | from func import myFunc 6 | 7 | cap = cv2.VideoCapture('./720p60hz.mp4') 8 | # cap = cv2.VideoCapture(0) 9 | modelPath = "./rknnModel/yolov5s_relu_tk2_RK3588_i8.rknn" 10 | # 线程数, 增大可提高帧率 11 | TPEs = 3 12 | # 初始化rknn池 13 | pool = rknnPoolExecutor( 14 | rknnModel=modelPath, 15 | TPEs=TPEs, 16 | func=myFunc) 17 | 18 | # 初始化异步所需要的帧 19 | if (cap.isOpened()): 20 | for i in range(TPEs + 1): 21 | ret, frame = cap.read() 22 | if not ret: 23 | cap.release() 24 | del pool 25 | exit(-1) 26 | pool.put(frame) 27 | 28 | frames, loopTime, initTime = 0, time.time(), time.time() 29 | while (cap.isOpened()): 30 | frames += 1 31 | ret, frame = cap.read() 32 | if not ret: 33 | break 34 | pool.put(frame) 35 | frame, flag = pool.get() 36 | if flag == False: 37 | break 38 | cv2.imshow('test', frame) 39 | if cv2.waitKey(1) & 0xFF == ord('q'): 40 | break 41 | if frames % 30 == 0: 42 | print("30帧平均帧率:\t", 30 / (time.time() - loopTime), "帧") 43 | loopTime = time.time() 44 | 45 | print("总平均帧率\t", frames / (time.time() - initTime)) 46 | # 释放cap和rknn线程池 47 | cap.release() 48 | cv2.destroyAllWindows() 49 | pool.release() 50 | -------------------------------------------------------------------------------- /performance.sh: -------------------------------------------------------------------------------- 1 | # 请切换到root用户 2 | 3 | # CPU定频 4 | echo "CPU0-3 可用频率:" 5 | sudo cat /sys/devices/system/cpu/cpufreq/policy0/scaling_available_frequencies 6 | sudo echo userspace > /sys/devices/system/cpu/cpufreq/policy0/scaling_governor 7 | sudo echo 1800000 > /sys/devices/system/cpu/cpufreq/policy0/scaling_setspeed 8 | echo "CPU0-3 当前频率:" 9 | sudo cat /sys/devices/system/cpu/cpufreq/policy0/cpuinfo_cur_freq 10 | 11 | echo "CPU4-5 可用频率:" 12 | sudo cat /sys/devices/system/cpu/cpufreq/policy4/scaling_available_frequencies 13 | sudo echo userspace > /sys/devices/system/cpu/cpufreq/policy4/scaling_governor 14 | sudo echo 2400000 > /sys/devices/system/cpu/cpufreq/policy4/scaling_setspeed 15 | echo "CPU4-5 当前频率:" 16 | sudo cat /sys/devices/system/cpu/cpufreq/policy4/cpuinfo_cur_freq 17 | 18 | echo "CPU6-7 可用频率:" 19 | sudo cat /sys/devices/system/cpu/cpufreq/policy6/scaling_available_frequencies 20 | sudo echo userspace > /sys/devices/system/cpu/cpufreq/policy6/scaling_governor 21 | sudo echo 2400000 > /sys/devices/system/cpu/cpufreq/policy6/scaling_setspeed 22 | echo "CPU6-7 当前频率:" 23 | sudo cat /sys/devices/system/cpu/cpufreq/policy6/cpuinfo_cur_freq 24 | 25 | # NPU定频 26 | echo "NPU 可用频率:" 27 | sudo cat /sys/class/devfreq/fdab0000.npu/available_frequencies 28 | sudo echo userspace > /sys/class/devfreq/fdab0000.npu/governor 29 | sudo echo 1000000000 > /sys/class/devfreq/fdab0000.npu/userspace/set_freq 30 | echo "NPU 当前频率:" 31 | sudo cat /sys/class/devfreq/fdab0000.npu/cur_freq -------------------------------------------------------------------------------- /rkcat.sh: -------------------------------------------------------------------------------- 1 | # 查看温度 2 | sensors 3 | # 查看NPU占用 4 | echo "当前NPU占用:" 5 | sudo cat /sys/kernel/debug/rknpu/load 6 | -------------------------------------------------------------------------------- /rknnModel/yolov5s_relu_tk2_RK3588_i8.rknn: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/leafqycc/rknn-multi-threaded/a8105849dab1d0fb39661e9bcbfb263a689eedc5/rknnModel/yolov5s_relu_tk2_RK3588_i8.rknn -------------------------------------------------------------------------------- /rknnpool.py: -------------------------------------------------------------------------------- 1 | from queue import Queue 2 | from rknnlite.api import RKNNLite 3 | from concurrent.futures import ThreadPoolExecutor, as_completed 4 | 5 | 6 | def initRKNN(rknnModel="./rknnModel/yolov5s.rknn", id=0): 7 | rknn_lite = RKNNLite() 8 | ret = rknn_lite.load_rknn(rknnModel) 9 | if ret != 0: 10 | print("Load RKNN rknnModel failed") 11 | exit(ret) 12 | if id == 0: 13 | ret = rknn_lite.init_runtime(core_mask=RKNNLite.NPU_CORE_0) 14 | elif id == 1: 15 | ret = rknn_lite.init_runtime(core_mask=RKNNLite.NPU_CORE_1) 16 | elif id == 2: 17 | ret = rknn_lite.init_runtime(core_mask=RKNNLite.NPU_CORE_2) 18 | elif id == -1: 19 | ret = rknn_lite.init_runtime(core_mask=RKNNLite.NPU_CORE_0_1_2) 20 | else: 21 | ret = rknn_lite.init_runtime() 22 | if ret != 0: 23 | print("Init runtime environment failed") 24 | exit(ret) 25 | print(rknnModel, "\t\tdone") 26 | return rknn_lite 27 | 28 | 29 | def initRKNNs(rknnModel="./rknnModel/yolov5s.rknn", TPEs=1): 30 | rknn_list = [] 31 | for i in range(TPEs): 32 | rknn_list.append(initRKNN(rknnModel, i % 3)) 33 | return rknn_list 34 | 35 | 36 | class rknnPoolExecutor(): 37 | def __init__(self, rknnModel, TPEs, func): 38 | self.TPEs = TPEs 39 | self.queue = Queue() 40 | self.rknnPool = initRKNNs(rknnModel, TPEs) 41 | self.pool = ThreadPoolExecutor(max_workers=TPEs) 42 | self.func = func 43 | self.num = 0 44 | 45 | def put(self, frame): 46 | self.queue.put(self.pool.submit( 47 | self.func, self.rknnPool[self.num % self.TPEs], frame)) 48 | self.num += 1 49 | 50 | def get(self): 51 | if self.queue.empty(): 52 | return None, False 53 | fut = self.queue.get() 54 | return fut.result(), True 55 | 56 | def release(self): 57 | self.pool.shutdown() 58 | for rknn_lite in self.rknnPool: 59 | rknn_lite.release() 60 | --------------------------------------------------------------------------------