v0.2.3 release

2026-01-25 10:40:40 +08:00
parent 782ef5e456
commit a516acb3ac
16 changed files with 30 additions and 103 deletions
@@ -18,14 +18,14 @@ https://anaconda.org/channels/nvidia/packages/cuda/overview
 conda install nvidia/label/cuda-12.9.0::cuda-toolkit nvidia::cudnn
 ```
 ## SDK安装方法
-1. 根据平台（win / linux）和python （如p38、p39、p310）版本下载对应的`.whl`文件
+1. 根据系统（win / linux）,平台(amd64, aarch64), python(如p38、p39、p310) 版本下载对应的`.whl`文件
 2. 运行pip命令安装：
 ```bash
-pip install orisys-{version}-{python-version}-{python-version}-{os}_amd64.whl
+pip install orisys-{version}-{python-version}-{python-version}-{os}_{machine}.whl
 ```
 如
 ```bash
-pip install orisys-0.2.0-cp310-cp310-win_amd64.whl
+pip install orisys-0.2.3-cp310-cp310-win_amd64.whl
 ```

 3. **安装 CuPy（根据您的 CUDA 版本选择）：**
@@ -184,6 +184,8 @@ centroid, contour, depth = sensor.read_info(
 * FSHEARX: X切向力，`float`。
 * FSHEARY: Y切向力，`float`。
 * FPS: 输出帧率，`float`。
+* CENTROID： 触碰点的坐标，(x, y)。
+* CONTOUR： 触碰区域轮廓，`np.ndarray`, shape=(H, W), 未生成时返回`np.empty`

 时间戳
 * TIMESTAMP: 时间戳字符串（HH:MM:SS），`str`。
@@ -198,7 +200,7 @@ centroid, contour, depth = sensor.read_info(
 返回值数量与有效参数数量一致。

 - 向量/图像类数据：`np.ndarray`  
-  - 若当前流程中尚未生成该数据，返回空数组 `np.array([])`
+  - 若当前流程中尚未生成该数据，返回空数组
 - 标量类数据：`float`
 - 时间戳：`str`（`TIMESTAMP`，格式为 `HH:MM:SS`）

@@ -280,3 +282,6 @@ A：`read_info()`按传入的`sensor.info`参数顺序返回一个元组。
 ### Q5:如果没有标定文件，或拼接结果不正确，会发生什么？
 A：若未指定或未找到标定文件，系统会在需要时创建新的拼接标定数据并保存到默认路径。
 拼接结果异常通常与标定数据、拼接配置或输入图像质量有关，建议重新生成拼接标定并检查配置参数。
+
+### Q6: 运行报错：“AttributeError: 'Stitcher' object has no attribute 'pos_default'”
+A: 请检查视频源的编号是否正确，以及是否能正常打开视频源。在linux 使用`v4l2-ctl --list-devices` 列出设备
@@ -16,7 +16,7 @@ def install_nuitka():
 def build():
    install_nuitka()
    
-    version = "0.2.2"
+    version = "0.2.3"
    src_dir = Path("src/orisys")
    output_dir = Path("build_nuitka")
    dist_dir = Path("dist_nuitka")
@@ -16,7 +16,7 @@ def install_nuitka():
 def build():
    install_nuitka()
    
-    version = "0.2.2"
+    version = "0.2.3"
    src_dir = Path("src/orisys")
    output_dir = Path("build_nuitka")
    dist_dir = Path("dist_nuitka")
@@ -18,7 +18,7 @@ def main():
    print("\n")
    print(f"Collecting data for device ID: {device_id} on test type: {test_type}, video source: {vid_source}")
    print("\n")
-    sensor = orisys.Sensor(vid_source, config_name="./config/prototype_of3.json", cal_path= f"./config/{sample_name}.npy", isstitch=True, cuda=True, verbose=True)
+    sensor = orisys.Sensor(vid_source, config_name="./config/prototype_of3.json", cal_path= f"./config/{sample_name}.npy", cuda=False, verbose=True)

    print(f"\n按 'q' 退出程序，按 'r' 重置光流追踪器，按 's' 开始保存，按 'e' 停止保存，按 'j' 减小力，按 'l' 增大力")
    force = 0 # kgf
@@ -1,39 +0,0 @@
-{
-  "name": "prototype",
-  "version": "1.0",
-  "camera": {
-    "resolution_raw": [1920, 1080],
-    "fps": 60,
-    "units": 15,
-    "units_used": 9, 
-    "resolution_stitch": [400, 400]
-  },
-  "stitcher": {
-    "min_area_frac": 0.018,
-    "max_area_frac": 0.035,
-    "max_aspect_ratio": 100,
-    "index": [1,2,3,6,7,8,11,12,13],
-    "margin": 10,
-    "nominal_ov_pos": 100,
-    "n": [3,3],
-    "row_tol": 0.4
-  },
-  "tracker": {
-    "adaptive": true,
-    "lower_threshold": 12.0,
-    "upper_threshold": 18.0,
-    "loop_closure_interval": 1,
-    "dis_preset": "medium",
-    "finest_scale": 1
-  },
-  "contact": {
-    "min_contour_area": 3000,
-    "flow_threshold":1,
-    "div_threshold":0.02,
-    "expansion_threshold": 0.01,
-    "kernel_size": [5,5],
-    "denoise_sigma": 15
-  }
-}
-
-
@@ -1,39 +0,0 @@
-{
-  "name": "prototype",
-  "version": "1.0",
-  "camera": {
-    "resolution_raw": [1920, 1080],
-    "fps": 60,
-    "units": 15,
-    "units_used": 9, 
-    "resolution_stitch": [400, 400]
-  },
-  "stitcher": {
-    "min_area_frac": 0.018,
-    "max_area_frac": 0.035,
-    "max_aspect_ratio": 100,
-    "index": [1,2,3,6,7,8,11,12,13],
-    "margin": 10,
-    "nominal_ov_pos": 100,
-    "n": [3,3],
-    "row_tol": 0.4
-  },
-  "tracker": {
-    "adaptive": true,
-    "lower_threshold": 12.0,
-    "upper_threshold": 18.0,
-    "loop_closure_interval": 1,
-    "dis_preset": "medium",
-    "finest_scale": 2
-  },
-  "contact": {
-    "min_contour_area": 3000,
-    "flow_threshold":1,
-    "div_threshold":0.02,
-    "expansion_threshold": 0.01,
-    "kernel_size": [5,5],
-    "denoise_sigma": 15
-  }
-}
-
-
@@ -3,7 +3,7 @@
  "version": "1.0",
  "camera": {
    "resolution_raw": [1920, 1080],
-    "fps": 60,
+    "fps": 30,
    "units": 15,
    "units_used": 9, 
    "resolution_stitch": [400, 400]
@@ -16,7 +16,7 @@
    "margin": 10,
    "nominal_ov_pos": 100,
    "n": [3,3],
-    "row_tol": 0.4
+    "row_tol": 0.6
  },
  "tracker": {
    "adaptive": true,
@@ -24,7 +24,7 @@
    "upper_threshold": 18.0,
    "loop_closure_interval": 1,
    "dis_preset": "medium",
-    "finest_scale": 3
+    "of_mode": 3
  },
  "contact": {
    "min_contour_area": 3000,
@@ -14,13 +14,14 @@ os.environ["OPENCV_VIDEOIO_MSMF_ENABLE_HW_TRANSFORMS"] = "0"
 import cv2
 import orisys
 import numpy as np
-import time
+
 def main():
+    # 步骤1：创建传感器对象 (必要步骤)，
+    # config_name为配置文件名（内置配置文件名）或路径（自定义配置文件路径）
+    # cal_path为校准文件路径, 每一个设备需要创建/使用一个校准文件

-    # 步骤1：创建传感器对象 (必要步骤)，config_name为配置文件名（内置配置文件名）或路径（自定义配置文件路径）
    # 方式1: 从视频文件读取
-    sensor = orisys.Sensor("s1.mp4", config_name="./config/prototype_of3.json", cal_path= "./config/cal.npy", isstitch=True, cuda=True, verbose=True)
-
+    sensor = orisys.Sensor("s1.mp4", config_name="./config/prototype_of3.json", cal_path= "./config/dd01a_0.npy", isstitch=True, cuda=False, verbose=True)

    # 方式2: 从摄像头读取（取消注释使用） 
    # sensor = orisys.Sensor(0, config_name="./config/prototype_of3.json", cal_path= "./config/cal.npy", isstitch=True, cuda=True, verbose=True)
@@ -9,7 +9,7 @@ if configs_dir.exists():

 setup(
    name="orisys",
-    version="0.2.2",
+    version="0.2.3",
    description="Orisys - Optical Tactile Sensor SDK",
    author="Your Name",
    package_dir={"": "src"},
@@ -5,7 +5,7 @@ A Python library for processing and analyzing optical tactile sensor data,
 including image stitching, optical flow tracking, and deformation decomposition.
 """

-__version__ = "0.2.2"
+__version__ = "0.2.3"
 __author__ = "Orisys"

 from .sensor import Sensor
@@ -3,7 +3,7 @@
  "version": "1.0",
  "camera": {
    "resolution_raw": [1920, 1080],
-    "fps": 60,
+    "fps": 30,
    "units": 15,
    "units_used": 9, 
    "resolution_stitch": [400, 400]
@@ -16,7 +16,7 @@
    "margin": 10,
    "nominal_ov_pos": 100,
    "n": [3,3],
-    "row_tol": 0.4
+    "row_tol": 0.6
  },
  "tracker": {
    "adaptive": true,
@@ -24,7 +24,7 @@
    "upper_threshold": 18.0,
    "loop_closure_interval": 1,
    "dis_preset": "medium",
-    "finest_scale": 1
+    "finest_scale": 3
  },
  "contact": {
    "min_contour_area": 3000,
@@ -35,7 +35,7 @@ class Tracker:
            
            
            # Aggressive optimization for CPU
-            self.__tracking_inst.setFinestScale(config_tracker["finest_scale"])      # Skip finest pyramid level (2x faster)
+            self.__tracking_inst.setFinestScale(config_tracker["of_mode"])      # Skip finest pyramid level (2x faster)
            # self.__tracking_inst.setPatchSize(8)        # Smaller patches (default 8)
            # self.__tracking_inst.setPatchStride(4)      # Larger stride = fewer patches
            # self.__tracking_inst.setGradientDescentIterations(12)  # Reduce iterations (default 25)
@@ -213,7 +213,6 @@ class Tracker:
            error = self.__getForwardBackwardError(
                self.__fine_base_frame_queue[i], frame, f)
            if error < self.__lower_threshold:
-                print("loop closed at frame ", str(i))
                self.__fine_base_frame_queue = self.__fine_base_frame_queue[:
                                                                            i +
                                                                            1]