From 0977a55cc23e95fc14f705e898cb3e87d81ecb9f Mon Sep 17 00:00:00 2001 From: russian_proger Date: Mon, 22 Dec 2025 12:46:34 +0300 Subject: [PATCH] feat: statistics --- main.py | 64 ++++++++++++++++++++++++++++++++++++++++++------- vision_chunk.py | 40 ++++++++++++++++++++++++++++++- 2 files changed, 94 insertions(+), 10 deletions(-) diff --git a/main.py b/main.py index 5cc9dee..8464edb 100644 --- a/main.py +++ b/main.py @@ -31,11 +31,39 @@ def main(): # make_global_photo('map.jpg') # Получаем траекторию от пользователя - points = get_trajectory_points('map.jpg') -# points = [np.float64(0.5443937502226799), np.float64(0.4030424838774785)], [np.float64(0.18517133490120316), np.float64(0.4586935604608052)], [np.float64(0.1641887171838272), np.float64(0.5586383510594329)], [np.float64(0.587198290366127), -# np.float64(0.5699957136274587)] - # points = [[np.float64(0.5028362002950056), np.float64(0.508463417020251)], [np.float64(0.5079239482442035), np.float64(0.508463417020251)], [np.float64(0.5045321162780716), np.float64(0.5210964284169014)], [np.float64(0.509054558899581), np.float64(0.5200436774671806)]] - # print(points) + # points = get_trajectory_points('map.jpg') + + # Trajectory #1 + points = [[np.float64(0.5384504359393909), np.float64(0.4084520767967683)], [np.float64(0.4451750568707629), np.float64(0.38213330305374654)], [np.float64(0.49266070439660997), np.float64(0.2789637099811013)], [np.float64(0.36377108968359656), np.float64(0.3263375027185404)], [np.float64(0.3535955937852008), np.float64(0.4337180995900692)]] + + # Trajectory #2 + # points = [[np.float64(0.29197731306713737), np.float64(0.3452870198135161)], [np.float64(0.33494051797147517), np.float64(0.2010601397017569)], [np.float64(0.39768940934491587), np.float64(0.25369768718780034)], [np.float64(0.4027771572941138), np.float64(0.4158213334448144)], [np.float64(0.2914120077394487), np.float64(0.5547844588079692)]] + + # Trajectory #3 + # points = [[np.float64(0.2755834585641664), np.float64(0.45687862048392835)], [np.float64(0.295934450360958), np.float64(0.5021469113219258)], [np.float64(0.32872215936689997), np.float64(0.4810918923275084)], [np.float64(0.3649017003389739), np.float64(0.5295184360146684)], [np.float64(0.3999506306556705), np.float64(0.49477765467387963)]] + + # Trajectory #4 + # points = [[np.float64(0.42143223310783934), np.float64(0.6663760594783815)], [np.float64(0.4253893704016599), np.float64(0.5537317078582484)], [np.float64(0.5124463908657128), np.float64(0.5621537154560153)], [np.float64(0.5124463908657128), np.float64(0.6684815613778233)], [np.float64(0.42143223310783934), np.float64(0.6663760594783815)]] + + # Trajectory #5 + # points = [[np.float64(0.5983728006743884), np.float64(0.7348048712102382)], [np.float64(0.5966768846913225), np.float64(0.5453097002604814)], [np.float64(0.6345523416464622), np.float64(0.7190136069644251)], [np.float64(0.6402053949233488), np.float64(0.5495207040593649)], [np.float64(0.5983728006743884), np.float64(0.7348048712102382)]] + + # Trajectory #6 + # points = [[np.float64(0.4406526142492536), np.float64(0.28106921188054296)], [np.float64(0.38581799746345413), np.float64(0.2968604761263561)], [np.float64(0.3931669667234066), np.float64(0.353709027411283)], [np.float64(0.4248240650739713), np.float64(0.35265627646156217)], [np.float64(0.40616898926024564), np.float64(0.3179154951207735)]] + + # Trajectory #7 + # points = [[np.float64(0.5491912371654754), np.float64(0.7505961354560512)], [np.float64(0.5537136797869846), np.float64(0.6863783275230781)], [np.float64(0.5017055896396284), np.float64(0.6653233085286606)], [np.float64(0.5520177638039186), np.float64(0.6042637534448503)], [np.float64(0.5593667330638712), np.float64(0.516885424618018)]] + + # Trajectory #8 + # points = + + # Trajectory #9 + # points = + + # Trajectory #10 + # points = + + print(points) # Для каждой точки сделаем приближенный снимок yandexMap = YandexMap() @@ -102,6 +130,12 @@ def main(): zoom_next_event = random.randint(5, 10) + errors = [] + chunk_errors = [] + chunk_improves = [] + + last_chunk_index = 0 + for i in range(10000000000): print(f"Image #{i}") if i == zoom_next_event: @@ -121,14 +155,20 @@ def main(): vis_manager.update_display() vis_manager.pause(0.2) - if command.stop: - break - vis_manager.set_target_index(pilot.target_idx) vis_manager.update_drone_trajectory(pilot.geo.x, pilot.geo.y) vis_manager.update_global_map(simulator.geo.x, simulator.geo.y) vis_manager.update_error_plot(i, pilot.geo.x, pilot.geo.y, simulator.geo.x, simulator.geo.y) + errors.append(np.hypot(pilot.geo.x - simulator.geo.x, pilot.geo.y - simulator.geo.y)) + if last_chunk_index != pilot.target_idx: + last_chunk_index = pilot.target_idx + chunk_errors.append(errors[-1]) + chunk_improves.append(errors[-1] - errors[max(len(errors) - 2, 0)]) + + if command.stop: + break + simulator.handle(command.dangle, command.velocity) vis_manager.update_display() @@ -137,7 +177,13 @@ def main(): last_proc_times = proc_time[-10:] print("Average FPS:", 1 / last_proc_times.mean()) + print("Errors:", errors) + print("MSE:", (np.array(errors) ** 2).mean()) + print("RMSE:", (np.array(errors) ** 2).mean() ** 0.5) + print("Chunk errors:", chunk_errors) + print("Chunk error improves:", chunk_improves) + print("Average FPS:", 1 / proc_time.mean()) vis_manager.show_final() if __name__ == "__main__": - main() \ No newline at end of file + main() diff --git a/vision_chunk.py b/vision_chunk.py index a123706..b4f8fc2 100644 --- a/vision_chunk.py +++ b/vision_chunk.py @@ -6,7 +6,7 @@ from pathlib import Path from typing import Literal, Optional, Tuple from PIL import Image -FeatureMethod = Literal["orb", "sift", "surf"] +FeatureMethod = Literal["orb", "sift", "surf", "akaze", "brisk"] @dataclass class VisionChunk: @@ -33,6 +33,36 @@ class VisionChunk: patchSize=31, fastThreshold=20, ) + elif self.feature_method == "sift": + self._detector = cv2.SIFT_create( + nfeatures=1000, + nOctaveLayers=3, + contrastThreshold=0.04, + edgeThreshold=10, + sigma=1.6 + ) + elif self.feature_method == "surf": + self._detector = cv2.xfeatures2d.SURF_create( + hessianThreshold=400.0, + nOctaveLayers=3, + # nOctaveLayers=4, + upright=False + ) + elif self.feature_method == "akaze": + self._detector = cv2.AKAZE_create( + descriptor_type=cv2.AKAZE_DESCRIPTOR_MLDB, + descriptor_size=0, + descriptor_channels=3, + threshold=0.001, + nOctaves=4, + diffusivity=cv2.KAZE_DIFF_PM_G2 + ) + elif self.feature_method == "brisk": + self._detector = cv2.BRISK_create( + thresh=30, + octaves=3, + patternScale=1.0 + ) else: raise ValueError(f"Unsupported feature method: {self.feature_method}") return self._detector @@ -40,6 +70,14 @@ class VisionChunk: def _get_matcher(self) -> cv2.DescriptorMatcher: if self._matcher is None: self._matcher = cv2.BFMatcher(cv2.NORM_HAMMING, crossCheck=False) + return self._matcher + if self.feature_method == 'orb': + self._matcher = cv2.BFMatcher(cv2.NORM_HAMMING, crossCheck=False) + elif self.feature_method == 'sift': + FLANN_INDEX_LSH = 6 + index_params = dict(algorithm=FLANN_INDEX_LSH, table_number=6, key_size=12, multi_probe_level=1) + search_params = dict(checks=50) + self._matcher = cv2.FlannBasedMatcher(index_params, search_params) return self._matcher def _preprocess(self, img_np: np.ndarray) -> np.ndarray: