make variables public, vesion variable and minor changes

Readme.md

@@ -5,12 +5,12 @@
 1. 根据平台和python 版本下载对应的`.whl`文件
 2. 运行pip命令安装：
 ```bash
-pip install orisys-{version}-{python}-none-{os}_amd64.whl
+pip install orisys-{version}-{python-version}-none-{os}_amd64.whl
 ```
 3. 并测试导入：
 ```python
 import orisys
-orisys.__version__
+print(orisys.__version__)
 ```
 ---
 ## `Sensor` 类别
@@ -39,7 +39,7 @@ sensor = Sensor("/data/data.mp4")
 
 ---
 
-## 2. `get_img` 方法
+## 2. `Sensor.get_img` 方法
 
 ### 描述
 
@@ -59,7 +59,7 @@ if img is None:
 ```
 ---
 
-## 3. `compute_deformation` 方法
+## 3. `Sensor.compute_deformation` 方法
 
 ### 描述
 
@@ -81,7 +81,7 @@ if img is None:
 sensor.compute_deformation()
 ```
 ---
-## 4. `compute_contact` 方法
+## 4. `Sensor.compute_contact` 方法
 
 ### 描述
 基于已计算的法向形变场进行接触区域分析，输出接触质心与轮廓等信息，并生成接触强度图。
@@ -120,7 +120,7 @@ centroid, contour, depth = sensor.read_info(
 )
 ```
 ---
-## 4. `read_info` 方法
+## 4. `Sensor.read_info` 方法
 
 ### 描述
 
@@ -176,7 +176,7 @@ flow = sensor.read_info(sensor.info.VRAW)
 ```
 ---
 
-## 5. `disconnect` 方法
+## 5. `Sensor.disconnect` 方法
 
 ### 描述
 
@@ -188,21 +188,7 @@ flow = sensor.read_info(sensor.info.VRAW)
 ---
 # 配置标定相关
 
-## 1. `export_config` 方法
+## 1. `list_config` 方法
-
-### 描述
-导出当前传感器实例使用的配置参数字典。
-
-### 输入参数
-* **config_name**: 需要导出的配置参数字典名字`str`
-* **path**: 导出的路径，默认`"./config/exported_config.json"`
-
-### 返回
-
-* `dict`: 导出的配置参数字典。
-
----
-## 2. `list_config` 方法
 
 ### 描述
 列出内置传感器配置参数字典。
@@ -210,6 +196,23 @@ flow = sensor.read_info(sensor.info.VRAW)
 ### 返回
 
 * `list`: 内置传感器配置参数字典的名字列表。
+---
+## 2. `export_config` 方法
+
+### 描述
+导出当前传感器实例使用的配置参数字典。
+
+### 输入参数
+* **config_name**: 需要导出的配置参数字典名字，`str`
+* **path**: 导出的路径，默认`"./config/exported_config.json"`
+
+### 返回
+
+* `dict`: 导出的配置参数字典。
+
+### 保存
+
+* 导出内置的`config_name`配置参数字典至`path`
 
 ---
 ---

build_multi_version.py

@@ -11,6 +11,9 @@ import platform
 from pathlib import Path
 
 
+# Package version
+VERSION = "0.2.0"
+
 # Python versions to build for
 PYTHON_VERSIONS = ['3.8', '3.9', '3.10']
 
@@ -157,7 +160,7 @@ def copy_additional_files():
         shutil.copytree('config', 'dist_obfuscated/config', dirs_exist_ok=True)
     
     # Copy README and other metadata files
-    files_to_copy = ['README.md', 'Readme(未完成).md', 'requirements.txt', 'LICENSE']
+    files_to_copy = ['README.md', 'requirements.txt', 'LICENSE']
     for file in files_to_copy:
         if os.path.exists(file):
             print(f"Copying {file}...")
@@ -217,7 +220,7 @@ for pkg in packages:
 
 setup(
     name="orisys",
-    version="0.2.0",
+    version="{VERSION}",
     description="Orisys - Optical Tactile Sensor SDK (Protected)",
     author="Your Name",
     package_dir={{"": "src"}},
@@ -335,7 +338,7 @@ def build_wheel_for_version(python_version):
         return False
     
     print(f"✅ Wheel for Python {python_version} on {PLATFORM_NAME} built successfully!")
-    print(f"   Expected: orisys-0.2.0-{py_tag}-none-{plat_tag}.whl")
+    print(f"   Expected: orisys-{VERSION}-{py_tag}-none-{plat_tag}.whl")
     return True
 
 
@@ -444,7 +447,7 @@ def main():
     for wheel in Path(f'dist/{PLATFORM_NAME}').glob('*.whl'):
         print(f"  - {wheel.name}")
     print("\nInstall with:")
-    print(f"  pip install dist/{PLATFORM_NAME}/orisys-0.2.0-*.whl")
+    print(f"  pip install dist/{PLATFORM_NAME}/orisys-{VERSION}-*.whl")
 
 
 if __name__ == '__main__':

src/orisys/__init__.py

@@ -1,5 +1,5 @@
 """
-Orisys - Optical Tactile Sensor SDK
+orisys - Optical Tactile Sensor SDK
 
 A Python library for processing and analyzing optical tactile sensor data,
 including image stitching, optical flow tracking, and deformation decomposition.
@@ -9,7 +9,6 @@ __version__ = "0.2.0"
 __author__ = "Orisys"
 
 from .sensor import Sensor
-from .MultiSensor import MultiSensor
 from . import util
 from . import configs
 
@@ -17,4 +16,14 @@ from . import configs
 list_config = configs.list_config
 export_config = configs.export_config
 
-__all__ = ['Sensor', 'MultiSensor', 'util', 'list_config', 'export_config']
+__all__ = [
+    # class
+    'Sensor', 
+
+    # util functions
+    'util',
+
+    # configs utilities functions
+    'list_config', 
+    'export_config'
+]

src/orisys/configs/__init__.py

@@ -67,6 +67,29 @@ def list_config():
     config_files = sorted(CONFIG_DIR.glob("*.json"))
     return [f.stem for f in config_files]
 
+def export_config(config_name = None, path="./config/exported_config.json"):
+    """
+    Export configuration to JSON file with readable formatting.
+    Arrays/lists are kept on a single line, while nested objects are indented.
+    
+    Args:
+        config: Configuration dictionary to export
+        path: Output file path (default: "./config/exported_config.json")
+    
+    Returns:
+        The exported config dictionary
+    """
+    config = load_config(config_name)
+    Path(path).parent.mkdir(parents=True, exist_ok=True)
+    
+    with open(path, 'w', encoding='utf-8') as f:
+        formatted = _format_json_value(config)
+        f.write(formatted)
+        f.write('\n')  # Add trailing newline
+    
+    print(f"Config name: {config_name} exported to {path}")
+    return config
+    
 def _format_json_value(value, indent_level=0, indent_str="    "):
     """
     Recursively format JSON value with arrays/lists on single line.
@@ -97,27 +120,3 @@ def _format_json_value(value, indent_level=0, indent_str="    "):
     else:
         # Primitive types (string, number, bool, None)
         return json.dumps(value, ensure_ascii=False)
-
-def export_config(config_name = None, path="./config/exported_config.json"):
-    """
-    Export configuration to JSON file with readable formatting.
-    Arrays/lists are kept on a single line, while nested objects are indented.
-    
-    Args:
-        config: Configuration dictionary to export
-        path: Output file path (default: "./config/exported_config.json")
-    
-    Returns:
-        The exported config dictionary
-    """
-    config = load_config(config_name)
-    Path(path).parent.mkdir(parents=True, exist_ok=True)
-    
-    with open(path, 'w', encoding='utf-8') as f:
-        formatted = _format_json_value(config)
-        f.write(formatted)
-        f.write('\n')  # Add trailing newline
-    
-    print(f"Config name: {config_name} exported to {path}")
-    return config
-    

src/orisys/sensor.py

@@ -92,21 +92,21 @@ class Sensor:
         self.compute_deformation_valid = False
         self.compute_contact_valid = False
         
-        # Data Variables
+        # Data Variables (public)
-        self.__img = None
+        self.img = None
-        self.__img_size_raw = None
+        self.img_size_raw = None
-        self.__img_filtered = None
+        self.img_filtered = None
-        self.__flow = None
+        self.flow = None
-        self.__vnormal = None
+        self.vnormal = None
-        self.__vshear = None
+        self.vshear = None
-        self.__n_boxes = None
+        self.n_boxes = None
-        self.__fnormal = self.__fshearx = self.__fsheary = self.__ftor = 0.0
+        self.fnormal = self.fshearx = self.fsheary = self.ftor = 0.0
 
-        # Contact Data Variables
+        # Contact Data Variables (public)
-        self.__centroid = None
+        self.centroid = None
-        self.__centroid_found = False
+        self.centroid_found = False
-        self.__contour = None
+        self.contour = None
-        self.__depth_map = None
+        self.depth_map = None
         
         # Timing
         self.last_log_time = time.perf_counter()
@@ -180,26 +180,26 @@ class Sensor:
         img = np.ascontiguousarray(self.__stitcher.stitch_rt_optimized())
         if log_timing: timings['stitch'] = (time.perf_counter() - t0) * 1000
 
-        self.__img_size_raw = img.shape
+        self.img_size_raw = img.shape
         # Resize
         img = cv2.resize(img, tuple(self._config_resolution_stitch), interpolation=cv2.INTER_CUBIC)
         
         # Temporal filtering (noise reduction)
         alpha = 0.7
-        if self.__img_filtered is None:
+        if self.img_filtered is None:
-            self.__img_filtered = img.astype(np.float32)
+            self.img_filtered = img.astype(np.float32)
         else:
-            self.__img_filtered = alpha * img + (1 - alpha) * self.__img_filtered
+            self.img_filtered = alpha * img + (1 - alpha) * self.img_filtered
         
-        self.__img = self.__img_filtered.astype(np.uint8)
+        self.img = self.img_filtered.astype(np.uint8)
 
         if log_timing:
             timings['total'] = (time.perf_counter() - t_start) * 1000
             self._print_timings("get_img", timings)
         if self.mirror:
-            self.__img = cv2.flip(self.__img, 1)
+            self.img = cv2.flip(self.img, 1)
             
-        return self.__img.copy()
+        return self.img.copy()
 
     def compute_deformation(self):
         """
@@ -208,7 +208,7 @@ class Sensor:
         Returns:
             np.ndarray: Optical flow field
         """
-        if self.__img is None:
+        if self.img is None:
             raise Exception("Warning: Get image first")
         
         self.__compute_flow()
@@ -220,17 +220,17 @@ class Sensor:
         return True
 
     def __compute_flow(self):
-        if self.__img is None:
+        if self.img is None:
             raise Exception("Warning: Get image first")
         
-        flow = self.__tracker.track(self.__img)
+        flow = self.__tracker.track(self.img)
         if hasattr(flow, 'download'):
             flow = flow.download()
-        self.__flow = flow
+        self.flow = flow
     
     def __compute_hhd(self):
 
-        flow = self.__flow
+        flow = self.flow
         if flow is None:
             raise Exception("Warning: Compute flow first")
         
@@ -243,11 +243,11 @@ class Sensor:
             _, forces = self.__hhd.get_force_gpu_v2(flow)
         else:
             _, forces = self.__hhd.get_force(flow)
-        self.__fnormal, self.__fshearx, self.__fsheary, self.__ftor = forces
+        self.fnormal, self.fshearx, self.fsheary, self.ftor = forces
         
         # Get components
-        self.__vnormal = self.__hhd.get_normal()
+        self.vnormal = self.__hhd.get_normal()
-        self.__vshear = self.__hhd.get_shear()
+        self.vshear = self.__hhd.get_shear()
 
         # Update state
         self.compute_deformation_valid = True
@@ -259,7 +259,7 @@ class Sensor:
         Compute contact information from vnormal field.
         
         Args:
-            vnormal: Optional vnormal field. If None, uses self.__vnormal.
+            vnormal: Optional vnormal field. If None, uses self.vnormal.
         
         Returns:
             dict: Contact result with centroid, contour, and depth_map
@@ -267,7 +267,7 @@ class Sensor:
         multiple_foe = False
         
         # Use provided vnormal or fall back to internal state
-        vnormal_to_use = vnormal if vnormal is not None else self.__vnormal
+        vnormal_to_use = vnormal if vnormal is not None else self.vnormal
         
         if vnormal_to_use is None:
             raise Exception("Warning: vnormal is required for contact computation")
@@ -280,11 +280,11 @@ class Sensor:
             else:
                 result = self.__contact3d.compute_foe(vnormal_to_use)
 
-        self.__centroid = result['centroid']
+        self.centroid = result['centroid']
-        self.__centroid_found = result['centroid_found']
+        self.centroid_found = result['centroid_found']
         if 'contour' in result:
-            self.__contour = result['contour']
+            self.contour = result['contour']
-        self.__depth_map = result['divergence_map']
+        self.depth_map = result['divergence_map']
 
         self.compute_contact_valid = True
         return result
@@ -301,7 +301,7 @@ class Sensor:
             Tuple: Requested data in order
         """
         if any(arg in [self.info.IMG] for arg in args):
-            if self.__img is None:
+            if self.img is None:
                 raise Exception("Warning: Get image first")
 
         if any(arg in [self.info.VRAW, self.info.VNORMAL, self.info.VSHEAR, self.info.FNORMAL, self.info.FSHEARX, self.info.FSHEARY] for arg in args):
@@ -314,26 +314,26 @@ class Sensor:
 
         mapping = {
             # Return copies of arrays to prevent external modification of internal state
-            self.info.VRAW: lambda: self.__flow.copy() if self.__flow is not None else np.array([]),
+            self.info.VRAW: lambda: self.flow.copy() if self.flow is not None else np.array([]),
-            self.info.VNORMAL: lambda: self.__vnormal.copy() if self.__vnormal is not None else np.array([]),
+            self.info.VNORMAL: lambda: self.vnormal.copy() if self.vnormal is not None else np.array([]),
-            self.info.VSHEAR: lambda: self.__vshear.copy() if self.__vshear is not None else np.array([]),
+            self.info.VSHEAR: lambda: self.vshear.copy() if self.vshear is not None else np.array([]),
             # Scalar values are safe to return directly
-            self.info.FNORMAL: lambda: self.__fnormal,
+            self.info.FNORMAL: lambda: self.fnormal,
-            self.info.FSHEARX: lambda: self.__fshearx,
+            self.info.FSHEARX: lambda: self.fshearx,
-            self.info.FSHEARY: lambda: self.__fsheary,
+            self.info.FSHEARY: lambda: self.fsheary,
             self.info.FPS: lambda: self._fps,
             self.info.TIMESTAMP: lambda: time.strftime('%H:%M:%S'),
             # Return copies of arrays to prevent external modification
-            self.info.DEPTH: lambda: self.__depth_map.copy() if self.__depth_map is not None else np.array([]),
+            self.info.DEPTH: lambda: self.depth_map.copy() if self.depth_map is not None else np.array([]),
             # Centroid: can be tuple, list, or array - return a copy to prevent modification
             # Return None if centroid is not found or empty
             self.info.CENTROID: lambda: (
-                np.array(self.__centroid).copy() 
+                np.array(self.centroid).copy() 
-                if self.__centroid is not None and len(self.__centroid) > 0 
+                if self.centroid is not None and len(self.centroid) > 0 
                 else None
             ),
-            self.info.CONTOUR: lambda: self.__contour.copy() if self.__contour is not None else np.array([]),
+            self.info.CONTOUR: lambda: self.contour.copy() if self.contour is not None else np.array([]),
-            self.info.IMG: lambda: self.__img.copy() if self.__img is not None else np.array([]),
+            self.info.IMG: lambda: self.img.copy() if self.img is not None else np.array([]),
         }
         
         return tuple(mapping.get(arg, lambda: None)() for arg in args if isinstance(arg, self.info))
@@ -475,7 +475,7 @@ class Sensor:
                 break
             v_mean0 = v_mean
         
-        self.__n_boxes = n_boxes
+        self.n_boxes = n_boxes
         self.stitch_valid = self.isstitch and n_boxes == self._config_units
         
         status = "valid for stitching" if self.stitch_valid else "non-stitch mode"
@@ -607,9 +607,9 @@ class Sensor:
     #                 continue
                 
     #             # Put the processed image in the queue
-    #             # get_img() updates self.__img, so we use that
+    #             # get_img() updates self.img, so we use that
-    #             if self.__img is not None:
+    #             if self.img is not None:
-    #                 self._queue_put(self._capture_queue, self.__img.copy())
+    #                 self._queue_put(self._capture_queue, self.img.copy())
     #         except Exception as e:
     #             if self.verbose: print(f"Capture error: {e}")
 
@@ -619,9 +619,9 @@ class Sensor:
     #         try:
     #             img = self._capture_queue.get(timeout=0.1)
     #             # Set __img to reuse __compute_flow()
-    #             self.__img = img
+    #             self.img = img
     #             self.__compute_flow()
-    #             flow = self.__flow.copy() if self.__flow is not None else None
+    #             flow = self.flow.copy() if self.flow is not None else None
     #             self._queue_put(self._flow_queue, (img, flow))
     #         except Empty:
     #             continue
@@ -635,16 +635,16 @@ class Sensor:
     #             img, flow = self._flow_queue.get(timeout=0.1)
                 
     #             # Set __flow to reuse __compute_hhd()
-    #             self.__flow = flow
+    #             self.flow = flow
     #             self.__compute_hhd()
     #             # Get results from internal variables set by __compute_hhd()
     #             result = {
     #                 'img': img, 'flow': flow,
-    #                 'normal': self.__vnormal.copy() if self.__vnormal is not None else None,
+    #                 'normal': self.vnormal.copy() if self.vnormal is not None else None,
-    #                 'shear': self.__vshear.copy() if self.__vshear is not None else None,
+    #                 'shear': self.vshear.copy() if self.vshear is not None else None,
     #                 # 'depth': getFilteredDensity(flow, use_cuda=self.cuda),
-    #                 'fnormal': self.__fnormal, 'fshearx': self.__fshearx,
+    #                 'fnormal': self.fnormal, 'fshearx': self.fshearx,
-    #                 'fsheary': self.__fsheary, 'ftor': self.__ftor,
+    #                 'fsheary': self.fsheary, 'ftor': self.ftor,
     #             }
                 
     #             # Always include contact fields to ensure consistent result structure

src/orisys/util.py

@@ -103,3 +103,4 @@ def draw_contact(image, contour, centroid, point_color=(0, 255, 0), region_color
         cv2.circle(image, (cx, cy), 10, point_color, 2)
     
     return image
+