diff --git a/config/compound_eye.png b/config/compound_eye.png index ef3b17b..452a7d4 100644 Binary files a/config/compound_eye.png and b/config/compound_eye.png differ diff --git a/config/prototype.json b/config/prototype.json deleted file mode 100644 index ff0b9c0..0000000 --- a/config/prototype.json +++ /dev/null @@ -1,31 +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": 20, - "index": [1,2,3,6,7,8,11,12,13], - "pos_default": [[260, 56], [577, 62], [897, 69], [1214, 75], [1530, 81], [256, 391], [570, 397], [889, 403], [1208, 409], [1523, 416], [248, 724], [563, 730], [882, 738], [1201, 743], [1516, 751]], - "margin": 10, - "nominal_ov_pos": 100 - }, - "contact": { - "min_contour_area": 3000, - "flow_threshold":1, - "div_threshold":0.02, - "expansion_threshold": 0.01, - "downsample_factor": 1, - "kernel_size": [5,5], - "denoise_sigma": 15 - } -} - - diff --git a/example1_basic.py b/example1_basic.py index 1ce3a87..e15e0c0 100644 --- a/example1_basic.py +++ b/example1_basic.py @@ -28,7 +28,7 @@ def main(): # verbose: 是否打印详细初始化日志 # 方式1: 从视频文件读取 - sensor = orisys.Sensor("./s1.mp4", isstitch=True, cuda=False, verbose=True,config_name="prototype") + sensor = orisys.Sensor("./s1.mp4", isstitch=True, cuda=True, verbose=True,config_name="prototype") # 方式2: 从摄像头读取（取消注释使用） # sensor = orisys.Sensor(0, isstitch=True, cuda=True, verbose=True) diff --git a/example_contact.py b/example_contact.py index 21f14c6..a011dc7 100644 --- a/example_contact.py +++ b/example_contact.py @@ -7,10 +7,10 @@ import time def main(): # 方式1: 从视频文件读取 - sensor = orisys.Sensor("./s1.mp4", isstitch=True, cuda=True, verbose=True,config_name="./config/prototype.json") + # sensor = orisys.Sensor("./s1.mp4", isstitch=True, cuda=True, verbose=True,config_name="prototype") # 方式2: 从摄像头读取（取消注释使用） - # sensor = orisys.Sensor(0, isstitch=True, cuda=False, verbose=True,config_name="./config/prototype.json") + sensor = orisys.Sensor(0, isstitch=True, cuda=True, verbose=True,config_name="prototype") print("\n按 'q' 退出程序，按 'r' 重置光流追踪器") @@ -20,32 +20,33 @@ def main(): # 步骤 2.2: 计算形变场 sensor.compute_deformation() + # 计算触碰点 + # sensor.compute_contact(min_magnitude=0.1,expansion_threshold=0.01,denoise_sigma=15) + sensor.compute_contact() - fps, flow, vnormal = sensor.read_info( + #计算后读取信息 + fps, flow, vnormal, img, contour, centroid, depth_map = sensor.read_info( sensor.info.FPS, sensor.info.VRAW, - sensor.info.VNORMAL + sensor.info.VNORMAL, + sensor.info.IMG, + sensor.info.CONTOUR, + sensor.info.CENTROID, + sensor.info.DEPTH ) arrows = orisys.util.draw_arrows( - sensor.img.copy(), # 使用 copy() 避免修改原图 + img, # 使用 copy() 避免修改原图 vnormal, threshold=5, grid_spacing=10, arrow_scale=1.0 ) cv2.imshow("形变场 Deformation", arrows) - - # 计算触碰点 - # sensor.compute_contact(min_magnitude=0.1,expansion_threshold=0.01,denoise_sigma=15) - sensor.compute_contact() # 在图像上触碰点和区域 - image_with_foe = orisys.util.draw_contact(sensor.img.copy(), sensor.contour, sensor.centroid) + image_with_foe = orisys.util.draw_contact(img, contour, centroid) cv2.imshow("Contact Centroid", image_with_foe) - - # 计算触碰区域 - depth_map = sensor.depth_map # 归一化散度值到0-255范围（使用绝对值，然后归一化） div_abs = depth_map diff --git a/src/orisys/Stitcher.py b/src/orisys/Stitcher.py index 3f4d25b..55545a4 100644 --- a/src/orisys/Stitcher.py +++ b/src/orisys/Stitcher.py @@ -6,7 +6,7 @@ import cv2 class Stitcher: - def __init__(self,isstitch=False, n=[3,3], config_stitcher=None,verbose=False): + def __init__(self,isstitch=False, config_stitcher=None,verbose=False): # Settings self.isstitch = isstitch @@ -22,8 +22,8 @@ class Stitcher: self.boxes = self.units = None self.index = config_stitcher["index"] self.stitch_calibration = self.tile_list = [] - self.ncol = n[0] - self.nrow = n[1] + self.ncol = config_stitcher["n"][0] + self.nrow = config_stitcher["n"][1] self.nominal_ov_pos=config_stitcher["nominal_ov_pos"] self.margin=config_stitcher["margin"] self.bound=self.nominal_ov_pos - self.margin diff --git a/src/orisys/configs/__init__.py b/src/orisys/configs/__init__.py index 130edfc..e5f05f7 100644 --- a/src/orisys/configs/__init__.py +++ b/src/orisys/configs/__init__.py @@ -47,10 +47,10 @@ def load_config(config_name_or_path): available = [f.stem for f in CONFIG_DIR.glob("*.json")] available_str = ", ".join(available) if available else "none" raise FileNotFoundError( - f"Config file not found: {config_name_or_path}\n" - f"Tried as file path: {config_path} (not found)\n" - f"Tried as package config: {package_config_path} (not found)\n" - f"Available package configs: {available_str}" + f"Input config file not found with name or path: {config_name_or_path}\n" + f" Tried as file path: {config_path} (not found)\n" + f" Tried as package config: {package_config_path} (not found)\n" + f" Available package configs: {available_str}" ) with open(package_config_path, 'r', encoding='utf-8') as f: diff --git a/src/orisys/configs/prototype.json b/src/orisys/configs/prototype.json index 59e9393..9b79c55 100644 --- a/src/orisys/configs/prototype.json +++ b/src/orisys/configs/prototype.json @@ -15,7 +15,8 @@ "index": [1,2,3,6,7,8,11,12,13], "pos_default": [[260, 56], [577, 62], [897, 69], [1214, 75], [1530, 81], [256, 391], [570, 397], [889, 403], [1208, 409], [1523, 416], [248, 724], [563, 730], [882, 738], [1201, 743], [1516, 751]], "margin": 10, - "nominal_ov_pos": 100 + "nominal_ov_pos": 100, + "n": [3,3] }, "contact": { "min_contour_area": 3000, diff --git a/src/orisys/sensor.py b/src/orisys/sensor.py index 04c7d61..96cd443 100644 --- a/src/orisys/sensor.py +++ b/src/orisys/sensor.py @@ -18,7 +18,6 @@ from queue import Queue, Empty from .Stitcher import Stitcher from .tracker import Tracker from .nHHD import nHHD -# from .getDensity import getFilteredDensity from . import configs from .get_depth import Contact3D @@ -48,6 +47,7 @@ class Sensor: CENTROID = auto() CONTOUR = auto() DEPTH = auto() + IMG = auto() # ========================================================================= # Initialization @@ -94,25 +94,24 @@ class Sensor: self.stitch_calibration = [] # Data Variables - self.img = None - self.img_size_raw = None - self.img_filtered = None - self.flow = None - self.vnormal = None - self.vshear = None - # self.depth = None - self.n_boxes = None - self.fnormal = self.fshearx = self.fsheary = self.ftor = 0.0 + self.__img = None + self.__img_size_raw = None + self.__img_filtered = None + self.__flow = None + self.__vnormal = None + self.__vshear = None + self.__n_boxes = None + self.__fnormal = self.__fshearx = self.__fsheary = self.__ftor = 0.0 # Contact Data Variables - self.centroid = None - self.centroid_found = False - self.contour = None - self.depth_map = None + self.__centroid = None + self.__centroid_found = False + self.__contour = None + self.__depth_map = None # Timing self.last_log_time = time.perf_counter() - self.fps = 0 + self._fps = 0 # Async pipeline state self._async_enabled = False @@ -125,17 +124,17 @@ class Sensor: self._stop_event = None # Load configuration - self.config_cam = None - self.config_stitcher = None - self.config_contact = None + self.__config_cam = None + self.__config_stitcher = None + self.__config_contact = None self._load_config() # Initialize components - self._stitcher = Stitcher(isstitch=isstitch, config_stitcher=self.config_stitcher, verbose=self.verbose) - self.tracker = Tracker(adaptive=True, cuda=cuda, verbose=self.verbose) - self.contact3d = Contact3D(config_contact=self.config_contact, verbose=self.verbose) - self.hhd = None + self.__stitcher = Stitcher(isstitch=isstitch, config_stitcher=self.__config_stitcher, verbose=self.verbose) + self.__tracker = Tracker(adaptive=True, cuda=cuda, verbose=self.verbose) + self.__contact3d = Contact3D(config_contact=self.__config_contact, verbose=self.verbose) + self.__hhd = None # Setup video capture self._open_video_source(override, box) @@ -174,35 +173,35 @@ class Sensor: # Extract and stitch tiles if log_timing: t0 = time.perf_counter() - self._stitcher.get_stitch_unit(gray) + self.__stitcher.get_stitch_unit(gray) self._extract_tiles(gray) if log_timing: timings['get_tiles'] = (time.perf_counter() - t0) * 1000 if log_timing: t0 = time.perf_counter() - img = np.ascontiguousarray(self._stitcher.stitch_rt_optimized()) + 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) + 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: - self.img_filtered = img.astype(np.float32) + if self.__img_filtered is None: + 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.imgupdate = True + self.__img = self.__img_filtered.astype(np.uint8) + self.__imgupdate = True 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 + return True def compute_deformation(self, log_timing=False): """ @@ -217,27 +216,27 @@ class Sensor: # Optical flow if log_timing: t0 = time.perf_counter() - flow = self.tracker.track(self.img) + flow = self.__tracker.track(self.__img) if hasattr(flow, 'download'): flow = flow.download() if log_timing: timings['optical_flow'] = (time.perf_counter() - t0) * 1000 # Initialize HHD solver - if self.hhd is None: - self.hhd = nHHD(grid=flow.shape[:2], spacings=(18, 18)) + if self.__hhd is None: + self.__hhd = nHHD(grid=flow.shape[:2], spacings=(18, 18)) # Force computation if log_timing: t0 = time.perf_counter() if self.cuda and self.CUPY_AVAILABLE: - _, forces = self.hhd.get_force_gpu_v2(flow) + _, forces = self.__hhd.get_force_gpu_v2(flow) else: - _, forces = self.hhd.get_force(flow) - self.fnormal, self.fshearx, self.fsheary, self.ftor = forces + _, forces = self.__hhd.get_force(flow) + self.__fnormal, self.__fshearx, self.__fsheary, self.__ftor = forces if log_timing: timings['hhd_decompose'] = (time.perf_counter() - t0) * 1000 # Get components - self.vnormal = self.hhd.get_normal() - self.vshear = self.hhd.get_shear() + self.__vnormal = self.__hhd.get_normal() + self.__vshear = self.__hhd.get_shear() # # Depth computation # if log_timing: t0 = time.perf_counter() @@ -245,40 +244,37 @@ class Sensor: # if log_timing: timings['get_density'] = (time.perf_counter() - t0) * 1000 # Update state - self.flow = flow + self.__flow = flow self.imgupdate = False self.vupdate = True # FPS calculation - self.fps = 1.0 / (time.perf_counter() - self.last_log_time) + self._fps = 1.0 / (time.perf_counter() - self.last_log_time) self.last_log_time = time.perf_counter() if log_timing: timings['total'] = (time.perf_counter() - t_start) * 1000 self._print_timings("compute_deformation", timings) - return self.flow + return True def compute_contact(self, multiple_foe=False, min_contour_area=3000, min_magnitude=1.0, expansion_threshold=0.01, downsample_factor=1, kernel_size=(5,5), denoise_sigma=15): if multiple_foe: - # result = compute_multiple_foe(self.vnormal, min_contour_area=min_contour_area, min_magnitude=min_magnitude, expansion_threshold=expansion_threshold, downsample_factor=downsample_factor, kernel_size=kernel_size, denoise_sigma=denoise_sigma) - result = self.contact3d.compute_multiple_foe(self.vnormal) + result = self.__contact3d.compute_multiple_foe(self.__vnormal) else: if self.cuda: - # result = compute_foe_gpu(self.vnormal, min_magnitude=min_magnitude, expansion_threshold=expansion_threshold, downsample_factor=downsample_factor, kernel_size=kernel_size, denoise_sigma=denoise_sigma) - result = self.contact3d.compute_foe_gpu(self.vnormal) + result = self.__contact3d.compute_foe_gpu(self.__vnormal) else: - # result = compute_foe(self.vnormal, min_magnitude=min_magnitude, expansion_threshold=expansion_threshold, downsample_factor=downsample_factor, kernel_size=kernel_size, denoise_sigma=denoise_sigma) - result = self.contact3d.compute_foe(self.vnormal) + result = self.__contact3d.compute_foe(self.__vnormal) - self.centroid = result['centroid'] - self.centroid_found = result['centroid_found'] + self.__centroid = result['centroid'] + self.__centroid_found = result['centroid_found'] if 'contour' in result: - self.contour = result['contour'] - self.depth_map = result['divergence_map'] + self.__contour = result['contour'] + self.__depth_map = result['divergence_map'] - return result + return True # def get_depth(self, denoise_sigma=15): @@ -295,10 +291,10 @@ class Sensor: self.get_img() self.compute_deformation() return { - 'img': self.img, 'flow': self.flow, - 'normal': self.vnormal, 'shear': self.vshear, 'depth': self.depth, - 'fps': self.fps, 'fnormal': self.fnormal, - 'fshearx': self.fshearx, 'fsheary': self.fsheary, 'ftor': self.ftor, + 'img': self.__img, 'flow': self.__flow, + 'normal': self.__vnormal, 'shear': self.__vshear, 'depth': self.__depth_map, + 'fps': self._fps, 'fnormal': self.__fnormal, + 'fshearx': self.__fshearx, 'fsheary': self.__fsheary, 'ftor': self.__ftor, } def read_info(self, *args) -> Tuple: @@ -315,17 +311,27 @@ class Sensor: print("Warning: Call compute_deformation() first.") mapping = { - self.info.VRAW: lambda: self.flow if self.flow is not None else np.array([]), - self.info.VNORMAL: lambda: self.vnormal if self.vnormal is not None else np.array([]), - self.info.VSHEAR: lambda: self.vshear if self.vshear is not None else np.array([]), - self.info.FNORMAL: lambda: self.fnormal, - self.info.FSHEARX: lambda: self.fshearx, - self.info.FSHEARY: lambda: self.fsheary, - self.info.FPS: lambda: self.fps, + # 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.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([]), + # Scalar values are safe to return directly + self.info.FNORMAL: lambda: self.__fnormal, + self.info.FSHEARX: lambda: self.__fshearx, + self.info.FSHEARY: lambda: self.__fsheary, + self.info.FPS: lambda: self._fps, self.info.TIMESTAMP: lambda: time.strftime('%H:%M:%S'), - self.info.DEPTH: lambda: self.depth_map if self.depth_map is not None else np.array([]), - self.info.CENTROID: lambda: self.centroid if self.centroid is not None else np.array([]), - self.info.CONTOUR: lambda: self.contour if self.contour is not None else np.array([]), + # 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([]), + # 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() + 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.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)) @@ -365,8 +371,8 @@ class Sensor: self._async_enabled = True self._capture_thread = Thread(target=self._capture_worker, daemon=True) - self._flow_thread = Thread(target=self._flow_worker, daemon=True) - self._compute_thread = Thread(target=self._hhd_worker, daemon=True) + self._flow_thread = Thread(target=self.__flow_worker, daemon=True) + self._compute_thread = Thread(target=self.__hhd_worker, daemon=True) self._contact_thread = Thread(target=self._contact_worker, daemon=True) self._capture_thread.start() @@ -419,7 +425,7 @@ class Sensor: def export_config(self, path="./config/exported_config.json"): """Return current configuration dict.""" - configs.export_config(self.config, path) + configs.export_config(self._config, path) if self.verbose: print(f"Config exported to {path}") return True @@ -437,11 +443,11 @@ class Sensor: if os.path.exists(self.cal_path): print("Loading calibration from", self.cal_path) self.stitch_calibration = np.load(self.cal_path, allow_pickle=True) - self._stitcher.stitch_calibration = self.stitch_calibration - return self._stitcher.stitch_rt_optimized() + self.__stitcher.stitch_calibration = self.stitch_calibration + return self.__stitcher.stitch_rt_optimized() else: print("Creating new calibration...") - img, self.stitch_calibration = self._stitcher.stitch_cal() + img, self.stitch_calibration = self.__stitcher.stitch_cal() os.makedirs("./config", exist_ok=True) np.save(self.cal_path, self.stitch_calibration) print("Calibration saved to", self.cal_path) @@ -453,30 +459,29 @@ class Sensor: def _load_config(self): """Load sensor configuration from JSON file.""" - self.config = configs.load_config(self.config_name) - cam = self.config["camera"] - self.config_resolution_raw = cam["resolution_raw"] - self.config_fps = cam["fps"] - self.config_units = cam["units"] - self.config_resolution_stitch = cam["resolution_stitch"] - # self.config_index = cam["index"] - # self.config_pos_default = cam["pos_default"] + self._config = configs.load_config(self.config_name) + cam = self._config["camera"] + self._config_resolution_raw = cam["resolution_raw"] + self._config_fps = cam["fps"] + self._config_units = cam["units"] + self._config_resolution_stitch = cam["resolution_stitch"] - self.config_stitcher = self.config["stitcher"] - self.config_contact = self.config["contact"] + self.__config_stitcher = self._config["stitcher"] + self.__config_contact = self._config["contact"] if self.verbose: print(f"Config: {self.config_name}") - print(f" Resolution: {self.config_resolution_raw} → {self.config_resolution_stitch}") - print(f" FPS: {self.config_fps}, Units: {self.config_units}") + print(f" Resolution: {self._config_resolution_raw} → {self._config_resolution_stitch}") + print(f" FPS: {self._config_fps}, Units: {self._config_units}") + return True def _open_video_source(self, override, box): """Initialize video capture and calibration.""" self.cap = cv2.VideoCapture(self.vid_src) self.cap.set(cv2.CAP_PROP_FOURCC, cv2.VideoWriter.fourcc('M', 'J', 'P', 'G')) - self.cap.set(cv2.CAP_PROP_FPS, self.config_fps) - self.cap.set(cv2.CAP_PROP_FRAME_WIDTH, self.config_resolution_raw[0]) - self.cap.set(cv2.CAP_PROP_FRAME_HEIGHT, self.config_resolution_raw[1]) + self.cap.set(cv2.CAP_PROP_FPS, self._config_fps) + self.cap.set(cv2.CAP_PROP_FRAME_WIDTH, self._config_resolution_raw[0]) + self.cap.set(cv2.CAP_PROP_FRAME_HEIGHT, self._config_resolution_raw[1]) if self.verbose: print("Connecting to video source...") @@ -493,8 +498,8 @@ class Sensor: if override: if box is not None: - self._stitcher.isstitch = self.isstitch = False - self._stitcher.boxes = box + self.__stitcher.isstitch = self.isstitch = False + self.__stitcher.boxes = box else: print("Override=True but no box provided.") else: @@ -507,21 +512,21 @@ class Sensor: n_boxes, v_mean0, timeout = 0, 0, 5 start_time = cv2.getTickCount() - while n_boxes < self.config_units: + while n_boxes < self._config_units: ret, frame = self.cap.read() v_mean = np.sum(cv2.mean(frame)) if abs(v_mean - v_mean0) < 5: - n_boxes = self._stitcher.find_stitch_boxes(frame, show=show) + n_boxes = self.__stitcher.find_stitch_boxes(frame, show=show) if (cv2.getTickCount() - start_time) / cv2.getTickFrequency() > timeout: print("Timeout finding vision units.") - self._stitcher.isstitch = self.isstitch = False + self.__stitcher.isstitch = self.isstitch = False break v_mean0 = v_mean - self.n_boxes = n_boxes - self.stitch_valid = self.isstitch and n_boxes == self.config_units + 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" print(f"Sensor: {status}") @@ -529,8 +534,8 @@ class Sensor: def _extract_tiles(self, img_src): """Extract tiles from source image.""" - self._stitcher.get_stitch_unit(img_src) - self._stitcher.extract_tiles() + self.__stitcher.get_stitch_unit(img_src) + self.__stitcher.extract_tiles() return True # ========================================================================= @@ -554,15 +559,15 @@ class Sensor: continue gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY) - self._stitcher.get_stitch_unit(gray) + self.__stitcher.get_stitch_unit(gray) self._extract_tiles(gray) - img = np.ascontiguousarray(self._stitcher.stitch_rt_optimized()) - img = cv2.resize(img, tuple(self.config_resolution_stitch), interpolation=cv2.INTER_CUBIC) + img = np.ascontiguousarray(self.__stitcher.stitch_rt_optimized()) + img = cv2.resize(img, tuple(self._config_resolution_stitch), interpolation=cv2.INTER_CUBIC) - if self.img_filtered is None: - self.img_filtered = img.astype(np.float32) + if self.__img_filtered is None: + 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._queue_put(self._capture_queue, self.img_filtered.astype(np.uint8)) except Exception as e: