From 29a79d6c04a741af026b6c27a59d36779c789ebb Mon Sep 17 00:00:00 2001
From: NYH <175484793@qq.com>
Date: Wed, 27 Dec 2023 13:49:59 +0800
Subject: [PATCH] code
---
.gitignore | 162 +++++++++++
.idea/.gitignore | 8 +
.idea/deployment.xml | 259 ++++++++++++++++++
.idea/inspectionProfiles/Project_Default.xml | 88 ++++++
.../inspectionProfiles/profiles_settings.xml | 6 +
.idea/misc.xml | 4 +
.idea/modules.xml | 8 +
.idea/rknn-multi-threaded-nosigmoid.iml | 12 +
LICENSE | 201 ++++++++++++++
README.md | 36 ++-
func.py | 221 +++++++++++++++
main.py | 49 ++++
performance.sh | 31 +++
rkcat.sh | 5 +
rknnModel/yolov5s_relu_tk2_RK3588_i8.rknn | Bin 0 -> 8460739 bytes
rknnpool.py | 59 ++++
16 files changed, 1148 insertions(+), 1 deletion(-)
create mode 100644 .gitignore
create mode 100644 .idea/.gitignore
create mode 100644 .idea/deployment.xml
create mode 100644 .idea/inspectionProfiles/Project_Default.xml
create mode 100644 .idea/inspectionProfiles/profiles_settings.xml
create mode 100644 .idea/misc.xml
create mode 100644 .idea/modules.xml
create mode 100644 .idea/rknn-multi-threaded-nosigmoid.iml
create mode 100644 LICENSE
create mode 100644 func.py
create mode 100644 main.py
create mode 100644 performance.sh
create mode 100644 rkcat.sh
create mode 100644 rknnModel/yolov5s_relu_tk2_RK3588_i8.rknn
create mode 100644 rknnpool.py
diff --git a/.gitignore b/.gitignore
new file mode 100644
index 0000000..deea617
--- /dev/null
+++ b/.gitignore
@@ -0,0 +1,162 @@
+# Byte-compiled / optimized / DLL files
+__pycache__/
+*.py[cod]
+*$py.class
+
+# C extensions
+*.so
+
+# Distribution / packaging
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+share/python-wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+MANIFEST
+
+# PyInstaller
+# Usually these files are written by a python script from a template
+# before PyInstaller builds the exe, so as to inject date/other infos into it.
+*.manifest
+*.spec
+
+# Installer logs
+pip-log.txt
+pip-delete-this-directory.txt
+
+# Unit test / coverage reports
+htmlcov/
+.tox/
+.nox/
+.coverage
+.coverage.*
+.cache
+nosetests.xml
+coverage.xml
+*.cover
+*.py,cover
+.hypothesis/
+.pytest_cache/
+cover/
+
+# Translations
+*.mo
+*.pot
+
+# Django stuff:
+*.log
+local_settings.py
+db.sqlite3
+db.sqlite3-journal
+
+# Flask stuff:
+instance/
+.webassets-cache
+
+# Scrapy stuff:
+.scrapy
+
+# Sphinx documentation
+docs/_build/
+
+# PyBuilder
+.pybuilder/
+target/
+
+# Jupyter Notebook
+.ipynb_checkpoints
+
+# IPython
+profile_default/
+ipython_config.py
+
+# pyenv
+# For a library or package, you might want to ignore these files since the code is
+# intended to run in multiple environments; otherwise, check them in:
+# .python-version
+
+# pipenv
+# According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
+# However, in case of collaboration, if having platform-specific dependencies or dependencies
+# having no cross-platform support, pipenv may install dependencies that don't work, or not
+# install all needed dependencies.
+#Pipfile.lock
+
+# poetry
+# Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control.
+# This is especially recommended for binary packages to ensure reproducibility, and is more
+# commonly ignored for libraries.
+# https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control
+#poetry.lock
+
+# pdm
+# Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control.
+#pdm.lock
+# pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it
+# in version control.
+# https://pdm.fming.dev/#use-with-ide
+.pdm.toml
+
+# PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm
+__pypackages__/
+
+# Celery stuff
+celerybeat-schedule
+celerybeat.pid
+
+# SageMath parsed files
+*.sage.py
+
+# Environments
+.env
+.venv
+env/
+venv/
+ENV/
+env.bak/
+venv.bak/
+
+# Spyder project settings
+.spyderproject
+.spyproject
+
+# Rope project settings
+.ropeproject
+
+# mkdocs documentation
+/site
+
+# mypy
+.mypy_cache/
+.dmypy.json
+dmypy.json
+
+# Pyre type checker
+.pyre/
+
+# pytype static type analyzer
+.pytype/
+
+# Cython debug symbols
+cython_debug/
+
+# PyCharm
+# JetBrains specific template is maintained in a separate JetBrains.gitignore that can
+# be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore
+# and can be added to the global gitignore or merged into this file. For a more nuclear
+# option (not recommended) you can uncomment the following to ignore the entire idea folder.
+#.idea/
+
+*.mp4
\ No newline at end of file
diff --git a/.idea/.gitignore b/.idea/.gitignore
new file mode 100644
index 0000000..13566b8
--- /dev/null
+++ b/.idea/.gitignore
@@ -0,0 +1,8 @@
+# Default ignored files
+/shelf/
+/workspace.xml
+# Editor-based HTTP Client requests
+/httpRequests/
+# Datasource local storage ignored files
+/dataSources/
+/dataSources.local.xml
diff --git a/.idea/deployment.xml b/.idea/deployment.xml
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diff --git a/.idea/inspectionProfiles/Project_Default.xml b/.idea/inspectionProfiles/Project_Default.xml
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diff --git a/.idea/inspectionProfiles/profiles_settings.xml b/.idea/inspectionProfiles/profiles_settings.xml
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diff --git a/.idea/misc.xml b/.idea/misc.xml
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diff --git a/.idea/modules.xml b/.idea/modules.xml
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diff --git a/.idea/rknn-multi-threaded-nosigmoid.iml b/.idea/rknn-multi-threaded-nosigmoid.iml
new file mode 100644
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\ No newline at end of file
diff --git a/LICENSE b/LICENSE
new file mode 100644
index 0000000..261eeb9
--- /dev/null
+++ b/LICENSE
@@ -0,0 +1,201 @@
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diff --git a/README.md b/README.md
index 64018c5..43d012f 100644
--- a/README.md
+++ b/README.md
@@ -1,2 +1,36 @@
-# Rknn-Multi-Threaded
+# 简介
+* 使用多线程异步操作rknn模型, 提高rk3588/rk3588s的NPU使用率, 进而提高推理帧数(rk3568之类修改后应该也能使用, 但是作者本人并没有rk3568开发板......)
+* 此分支使用模型[yolov5s_relu_tk2_RK3588_i8.rknn](https://github.com/airockchip/rknn_model_zoo), 将yolov5s模型的激活函数silu修改为为relu,在损失一点精度的情况下获得较大性能提升,详情见于[rknn_model_zoo](https://github.com/airockchip/rknn_model_zoo/tree/main/models/CV/object_detection/yolo)
+* 此项目的[c++](https://github.com/leafqycc/rknn-cpp-Multithreading)实现
+# 更新说明
+* 无
+
+
+# 使用说明
+### 演示
+ * 将仓库拉取至本地, 并将Releases中的演示视频放于项目根目录下, 运行main.py查看演示示例
+ * 切换至root用户运行performance.sh可以进行定频操作(约等于开启性能模式)
+ * 运行rkcat.sh可以查看当前温度与NPU占用
+### 部署应用
+ * 修改main.py下的modelPath为你自己的模型所在路径
+ * 修改main.py下的cap为你想要运行的视频/摄像头
+ * 修改main.py下的TPEs为你想要的线程数, 具体可参考下表
+ * 修改func.py为你自己需要的推理函数, 具体可查看myFunc函数
+
+# 多线程模型帧率测试
+* 使用performance.sh进行CPU/NPU定频尽量减少误差
+* 测试模型为[yolov5s_relu_tk2_RK3588_i8.rknn](https://github.com/airockchip/rknn_model_zoo)
+* 测试视频见于Releases
+
+| 模型\线程数 | 1 | 2 | 3 | 4 | 5 | 6 |
+| ---- | ---- | ---- | ---- | ---- | ---- | ---- |
+| yolov5s | 27.4491 | 49.0747 | 65.3673 | 63.3204 | 71.8407 | 72.0590 |
+
+# 补充
+* 多线程下CPU, NPU占用较高, **核心温度相应增高**, 请做好散热。推荐开1, 2, 3线程, 实测小铜片散热下运行三分钟温度约为56°, 64°, 69°
+
+# Acknowledgements
+* https://github.com/ultralytics/yolov5
+* https://github.com/rockchip-linux/rknn-toolkit2
+* https://github.com/airockchip/rknn_model_zoo
\ No newline at end of file
diff --git a/func.py b/func.py
new file mode 100644
index 0000000..751bc98
--- /dev/null
+++ b/func.py
@@ -0,0 +1,221 @@
+#以下代码改自https://github.com/rockchip-linux/rknn-toolkit2/tree/master/examples/onnx/yolov5
+import cv2
+import numpy as np
+
+OBJ_THRESH, NMS_THRESH, IMG_SIZE = 0.25, 0.45, 640
+
+CLASSES = ("person", "bicycle", "car", "motorbike ", "aeroplane ", "bus ", "train", "truck ", "boat", "traffic light",
+ "fire hydrant", "stop sign ", "parking meter", "bench", "bird", "cat", "dog ", "horse ", "sheep", "cow", "elephant",
+ "bear", "zebra ", "giraffe", "backpack", "umbrella", "handbag", "tie", "suitcase", "frisbee", "skis", "snowboard", "sports ball", "kite",
+ "baseball bat", "baseball glove", "skateboard", "surfboard", "tennis racket", "bottle", "wine glass", "cup", "fork", "knife ",
+ "spoon", "bowl", "banana", "apple", "sandwich", "orange", "broccoli", "carrot", "hot dog", "pizza ", "donut", "cake", "chair", "sofa",
+ "pottedplant", "bed", "diningtable", "toilet ", "tvmonitor", "laptop ", "mouse ", "remote ", "keyboard ", "cell phone", "microwave ",
+ "oven ", "toaster", "sink", "refrigerator ", "book", "clock", "vase", "scissors ", "teddy bear ", "hair drier", "toothbrush ")
+
+
+#
+# def sigmoid(x):
+# return 1 / (1 + np.exp(-x))
+
+
+def xywh2xyxy(x):
+ # Convert [x, y, w, h] to [x1, y1, x2, y2]
+ y = np.copy(x)
+ y[:, 0] = x[:, 0] - x[:, 2] / 2 # top left x
+ y[:, 1] = x[:, 1] - x[:, 3] / 2 # top left y
+ y[:, 2] = x[:, 0] + x[:, 2] / 2 # bottom right x
+ y[:, 3] = x[:, 1] + x[:, 3] / 2 # bottom right y
+ return y
+
+
+def process(input, mask, anchors):
+
+ anchors = [anchors[i] for i in mask]
+ grid_h, grid_w = map(int, input.shape[0:2])
+
+ box_confidence = input[..., 4]
+ box_confidence = np.expand_dims(box_confidence, axis=-1)
+
+ box_class_probs = input[..., 5:]
+
+ box_xy = input[..., :2] *2 - 0.5
+
+ col = np.tile(np.arange(0, grid_w), grid_w).reshape(-1, grid_w)
+ row = np.tile(np.arange(0, grid_h).reshape(-1, 1), grid_h)
+ col = col.reshape(grid_h, grid_w, 1, 1).repeat(3, axis=-2)
+ row = row.reshape(grid_h, grid_w, 1, 1).repeat(3, axis=-2)
+ grid = np.concatenate((col, row), axis=-1)
+ box_xy += grid
+ box_xy *= int(IMG_SIZE/grid_h)
+
+ box_wh = pow(input[..., 2:4] *2, 2)
+ box_wh = box_wh * anchors
+
+ return np.concatenate((box_xy, box_wh), axis=-1), box_confidence, box_class_probs
+
+
+def filter_boxes(boxes, box_confidences, box_class_probs):
+ """Filter boxes with box threshold. It's a bit different with origin yolov5 post process!
+
+ # Arguments
+ boxes: ndarray, boxes of objects.
+ box_confidences: ndarray, confidences of objects.
+ box_class_probs: ndarray, class_probs of objects.
+
+ # Returns
+ boxes: ndarray, filtered boxes.
+ classes: ndarray, classes for boxes.
+ scores: ndarray, scores for boxes.
+ """
+ boxes = boxes.reshape(-1, 4)
+ box_confidences = box_confidences.reshape(-1)
+ box_class_probs = box_class_probs.reshape(-1, box_class_probs.shape[-1])
+
+ _box_pos = np.where(box_confidences >= OBJ_THRESH)
+ boxes = boxes[_box_pos]
+ box_confidences = box_confidences[_box_pos]
+ box_class_probs = box_class_probs[_box_pos]
+
+ class_max_score = np.max(box_class_probs, axis=-1)
+ classes = np.argmax(box_class_probs, axis=-1)
+ _class_pos = np.where(class_max_score >= OBJ_THRESH)
+
+ return boxes[_class_pos], classes[_class_pos], (class_max_score * box_confidences)[_class_pos]
+
+
+def nms_boxes(boxes, scores):
+ """Suppress non-maximal boxes.
+
+ # Arguments
+ boxes: ndarray, boxes of objects.
+ scores: ndarray, scores of objects.
+
+ # Returns
+ keep: ndarray, index of effective boxes.
+ """
+ x = boxes[:, 0]
+ y = boxes[:, 1]
+ w = boxes[:, 2] - boxes[:, 0]
+ h = boxes[:, 3] - boxes[:, 1]
+
+ areas = w * h
+ order = scores.argsort()[::-1]
+
+ keep = []
+ while order.size > 0:
+ i = order[0]
+ keep.append(i)
+
+ xx1 = np.maximum(x[i], x[order[1:]])
+ yy1 = np.maximum(y[i], y[order[1:]])
+ xx2 = np.minimum(x[i] + w[i], x[order[1:]] + w[order[1:]])
+ yy2 = np.minimum(y[i] + h[i], y[order[1:]] + h[order[1:]])
+
+ w1 = np.maximum(0.0, xx2 - xx1 + 0.00001)
+ h1 = np.maximum(0.0, yy2 - yy1 + 0.00001)
+ inter = w1 * h1
+
+ ovr = inter / (areas[i] + areas[order[1:]] - inter)
+ inds = np.where(ovr <= NMS_THRESH)[0]
+ order = order[inds + 1]
+ return np.array(keep)
+
+
+def yolov5_post_process(input_data):
+ masks = [[0, 1, 2], [3, 4, 5], [6, 7, 8]]
+ anchors = [[10, 13], [16, 30], [33, 23], [30, 61], [62, 45],
+ [59, 119], [116, 90], [156, 198], [373, 326]]
+
+ boxes, classes, scores = [], [], []
+ for input, mask in zip(input_data, masks):
+ b, c, s = process(input, mask, anchors)
+ b, c, s = filter_boxes(b, c, s)
+ boxes.append(b)
+ classes.append(c)
+ scores.append(s)
+
+ boxes = np.concatenate(boxes)
+ boxes = xywh2xyxy(boxes)
+ classes = np.concatenate(classes)
+ scores = np.concatenate(scores)
+
+ nboxes, nclasses, nscores = [], [], []
+ for c in set(classes):
+ inds = np.where(classes == c)
+ b = boxes[inds]
+ c = classes[inds]
+ s = scores[inds]
+
+ keep = nms_boxes(b, s)
+
+ nboxes.append(b[keep])
+ nclasses.append(c[keep])
+ nscores.append(s[keep])
+
+ if not nclasses and not nscores:
+ return None, None, None
+
+ return np.concatenate(nboxes), np.concatenate(nclasses), np.concatenate(nscores)
+
+
+def draw(image, boxes, scores, classes):
+ for box, score, cl in zip(boxes, scores, classes):
+ top, left, right, bottom = box
+ # print('class: {}, score: {}'.format(CLASSES[cl], score))
+ # print('box coordinate left,top,right,down: [{}, {}, {}, {}]'.format(top, left, right, bottom))
+ top = int(top)
+ left = int(left)
+
+ cv2.rectangle(image, (top, left), (int(right), int(bottom)), (255, 0, 0), 2)
+ cv2.putText(image, '{0} {1:.2f}'.format(CLASSES[cl], score),
+ (top, left - 6),
+ cv2.FONT_HERSHEY_SIMPLEX,
+ 0.6, (0, 0, 255), 2)
+
+def letterbox(im, new_shape=(640, 640), color=(0, 0, 0)):
+ shape = im.shape[:2] # current shape [height, width]
+ if isinstance(new_shape, int):
+ new_shape = (new_shape, new_shape)
+
+ r = min(new_shape[0] / shape[0], new_shape[1] / shape[1])
+
+ ratio = r, r # width, height ratios
+ new_unpad = int(round(shape[1] * r)), int(round(shape[0] * r))
+ dw, dh = new_shape[1] - new_unpad[0], new_shape[0] - \
+ new_unpad[1] # wh padding
+
+ dw /= 2 # divide padding into 2 sides
+ dh /= 2
+
+ if shape[::-1] != new_unpad: # resize
+ im = cv2.resize(im, new_unpad, interpolation=cv2.INTER_LINEAR)
+ top, bottom = int(round(dh - 0.1)), int(round(dh + 0.1))
+ left, right = int(round(dw - 0.1)), int(round(dw + 0.1))
+ im = cv2.copyMakeBorder(im, top, bottom, left, right,
+ cv2.BORDER_CONSTANT, value=color) # add border
+ return im
+ # return im, ratio, (dw, dh)
+
+def myFunc(rknn_lite, IMG):
+ IMG = cv2.cvtColor(IMG, cv2.COLOR_BGR2RGB)
+ # 等比例缩放
+ # IMG = letterbox(IMG)
+ # 强制放缩
+ IMG = cv2.resize(IMG, (IMG_SIZE, IMG_SIZE))
+ outputs = rknn_lite.inference(inputs=[IMG])
+
+ input0_data = outputs[0].reshape([3, -1]+list(outputs[0].shape[-2:]))
+ input1_data = outputs[1].reshape([3, -1]+list(outputs[1].shape[-2:]))
+ input2_data = outputs[2].reshape([3, -1]+list(outputs[2].shape[-2:]))
+
+ input_data = list()
+ input_data.append(np.transpose(input0_data, (2, 3, 0, 1)))
+ input_data.append(np.transpose(input1_data, (2, 3, 0, 1)))
+ input_data.append(np.transpose(input2_data, (2, 3, 0, 1)))
+
+ boxes, classes, scores = yolov5_post_process(input_data)
+
+ IMG = cv2.cvtColor(IMG, cv2.COLOR_RGB2BGR)
+ if boxes is not None:
+ draw(IMG, boxes, scores, classes)
+ return IMG
diff --git a/main.py b/main.py
new file mode 100644
index 0000000..d685539
--- /dev/null
+++ b/main.py
@@ -0,0 +1,49 @@
+import cv2
+import time
+from rknnpool import rknnPoolExecutor
+# 图像处理函数，实际应用过程中需要自行修改
+from func import myFunc
+
+cap = cv2.VideoCapture('./720p60hz.mp4')
+# cap = cv2.VideoCapture(0)
+modelPath = "./rknnModel/yolov5s_relu_tk2_RK3588_i8.rknn"
+# 线程数, 增大可提高帧率
+TPEs = 3
+# 初始化rknn池
+pool = rknnPoolExecutor(
+ rknnModel=modelPath,
+ TPEs=TPEs,
+ func=myFunc)
+
+# 初始化异步所需要的帧
+if (cap.isOpened()):
+ for i in range(TPEs + 1):
+ ret, frame = cap.read()
+ if not ret:
+ cap.release()
+ del pool
+ exit(-1)
+ pool.put(frame)
+
+frames, loopTime, initTime = 0, time.time(), time.time()
+while (cap.isOpened()):
+ frames += 1
+ ret, frame = cap.read()
+ if not ret:
+ break
+ pool.put(frame)
+ frame, flag = pool.get()
+ if flag == False:
+ break
+ cv2.imshow('test', frame)
+ if cv2.waitKey(1) & 0xFF == ord('q'):
+ break
+ if frames % 30 == 0:
+ print("30帧平均帧率:\t", 30 / (time.time() - loopTime), "帧")
+ loopTime = time.time()
+
+print("总平均帧率\t", frames / (time.time() - initTime))
+# 释放cap和rknn线程池
+cap.release()
+cv2.destroyAllWindows()
+pool.release()
diff --git a/performance.sh b/performance.sh
new file mode 100644
index 0000000..325c918
--- /dev/null
+++ b/performance.sh
@@ -0,0 +1,31 @@
+# 请切换到root用户
+
+# CPU定频
+echo "CPU0-3 可用频率:"
+sudo cat /sys/devices/system/cpu/cpufreq/policy0/scaling_available_frequencies
+sudo echo userspace > /sys/devices/system/cpu/cpufreq/policy0/scaling_governor
+sudo echo 1800000 > /sys/devices/system/cpu/cpufreq/policy0/scaling_setspeed
+echo "CPU0-3 当前频率:"
+sudo cat /sys/devices/system/cpu/cpufreq/policy0/cpuinfo_cur_freq
+
+echo "CPU4-5 可用频率:"
+sudo cat /sys/devices/system/cpu/cpufreq/policy4/scaling_available_frequencies
+sudo echo userspace > /sys/devices/system/cpu/cpufreq/policy4/scaling_governor
+sudo echo 2400000 > /sys/devices/system/cpu/cpufreq/policy4/scaling_setspeed
+echo "CPU4-5 当前频率:"
+sudo cat /sys/devices/system/cpu/cpufreq/policy4/cpuinfo_cur_freq
+
+echo "CPU6-7 可用频率:"
+sudo cat /sys/devices/system/cpu/cpufreq/policy6/scaling_available_frequencies
+sudo echo userspace > /sys/devices/system/cpu/cpufreq/policy6/scaling_governor
+sudo echo 2400000 > /sys/devices/system/cpu/cpufreq/policy6/scaling_setspeed
+echo "CPU6-7 当前频率:"
+sudo cat /sys/devices/system/cpu/cpufreq/policy6/cpuinfo_cur_freq
+
+# NPU定频
+echo "NPU 可用频率:"
+sudo cat /sys/class/devfreq/fdab0000.npu/available_frequencies
+sudo echo userspace > /sys/class/devfreq/fdab0000.npu/governor
+sudo echo 1000000000 > /sys/class/devfreq/fdab0000.npu/userspace/set_freq
+echo "NPU 当前频率:"
+sudo cat /sys/class/devfreq/fdab0000.npu/cur_freq
\ No newline at end of file
diff --git a/rkcat.sh b/rkcat.sh
new file mode 100644
index 0000000..66abb15
--- /dev/null
+++ b/rkcat.sh
@@ -0,0 +1,5 @@
+# 查看温度
+sensors
+# 查看NPU占用
+echo "当前NPU占用:"
+sudo cat /sys/kernel/debug/rknpu/load
diff --git a/rknnModel/yolov5s_relu_tk2_RK3588_i8.rknn b/rknnModel/yolov5s_relu_tk2_RK3588_i8.rknn
new file mode 100644
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