From c6fbfe8c70b5f75de7060bc3a62b3b8aedbe34f3 Mon Sep 17 00:00:00 2001 From: Prohurtz <48768484+RedHawk989@users.noreply.github.com> Date: Thu, 28 Sep 2023 13:19:12 -0500 Subject: [PATCH] fix: left eye ransac thresh set to right --- EyeTrackApp/ransac.py | 278 +++++++++++++++++++++++++----------------- 1 file changed, 165 insertions(+), 113 deletions(-) diff --git a/EyeTrackApp/ransac.py b/EyeTrackApp/ransac.py index f8db31c..2ff8b77 100644 --- a/EyeTrackApp/ransac.py +++ b/EyeTrackApp/ransac.py @@ -1,4 +1,4 @@ -''' +""" ------------------------------------------------------------------------------------------------------ ,@@@@@@ @@ -24,7 +24,7 @@ Algorithm App Implementations By: Prohurtz, qdot (Initial App Creator) Copyright (c) 2023 EyeTrackVR <3 ------------------------------------------------------------------------------------------------------ -''' +""" import cv2 import numpy as np from enum import IntEnum @@ -35,7 +35,7 @@ import psutil import sys process = psutil.Process(os.getpid()) # set process priority to low -try: # medium chance this does absolutely nothing but eh +try: # medium chance this does absolutely nothing but eh sys.getwindowsversion() except AttributeError: process.nice(0) # UNIX: 0 low 10 high @@ -44,11 +44,14 @@ else: process.nice(psutil.BELOW_NORMAL_PRIORITY_CLASS) # Windows process.nice() + class EyeId(IntEnum): RIGHT = 0 LEFT = 1 BOTH = 2 SETTINGS = 3 + + def ellipse_model(data, y, f): """ There is no need to make this process a function, since making the process a function will slow it down a little by calling it. @@ -61,60 +64,87 @@ def ellipse_model(data, y, f): """ return data.dot(y) + f + # @profile -def fit_rotated_ellipse_ransac(data: np.ndarray, rng: np.random.Generator, iter=100, sample_num=10, offset=80 # 80.0, 10, 80 - ): # before changing these values, please read up on the ransac algorithm +def fit_rotated_ellipse_ransac( + data: np.ndarray, + rng: np.random.Generator, + iter=100, + sample_num=10, + offset=80, # 80.0, 10, 80 +): # before changing these values, please read up on the ransac algorithm # However if you want to change any value just know that higher iterations will make processing frames slower effective_sample = None - + # The array contents do not change during the loop, so only one call is needed. # They say len is faster than shape. # Reference url: https://stackoverflow.com/questions/35547853/what-is-faster-python3s-len-or-numpys-shape len_data = len(data) - + if len_data < sample_num: return None - + # Type of calculation result ret_dtype = np.float64 - + # Sorts a random number array of size (iter,len_data). After sorting, returns the index of sample_num random numbers before sorting. # If the array size is less than about 100, this is faster than rng.choice. rng_sample = rng.random((iter, len_data)).argsort()[:, :sample_num] # or # I don't see any advantage to doing this. # rng_sample = np.asarray(rng.random((iter, len_data)).argsort()[:, :sample_num], dtype=np.int32) - + # I don't think it looks beautiful. # x,y,x**2,y**2,x*y,1,-1*x**2 datamod = np.concatenate( - [data, data ** 2, (data[:, 0] * data[:, 1])[:, np.newaxis], np.ones((len_data, 1), dtype=ret_dtype), - (-1 * data[:, 0] ** 2)[:, np.newaxis]], axis=1, - dtype=ret_dtype) - + [ + data, + data**2, + (data[:, 0] * data[:, 1])[:, np.newaxis], + np.ones((len_data, 1), dtype=ret_dtype), + (-1 * data[:, 0] ** 2)[:, np.newaxis], + ], + axis=1, + dtype=ret_dtype, + ) + datamod_slim = np.array(datamod[:, :5], dtype=ret_dtype) - + datamod_rng = datamod[rng_sample] datamod_rng6 = datamod_rng[:, :, 6] datamod_rng_swap = datamod_rng[:, :, [4, 3, 0, 1, 5]] datamod_rng_swap_trans = datamod_rng_swap.transpose((0, 2, 1)) - + # These two lines are one of the bottlenecks datamod_rng_5x5 = np.matmul(datamod_rng_swap_trans, datamod_rng_swap) - datamod_rng_p5smp = np.matmul(np.linalg.inv(datamod_rng_5x5), datamod_rng_swap_trans) - - datamod_rng_p = np.matmul(datamod_rng_p5smp, datamod_rng6[:, :, np.newaxis]).reshape((-1, 5)) - + datamod_rng_p5smp = np.matmul( + np.linalg.inv(datamod_rng_5x5), datamod_rng_swap_trans + ) + + datamod_rng_p = np.matmul( + datamod_rng_p5smp, datamod_rng6[:, :, np.newaxis] + ).reshape((-1, 5)) + # I don't think it looks beautiful. ellipse_y_arr = np.asarray( - [datamod_rng_p[:, 2], datamod_rng_p[:, 3], np.ones(len(datamod_rng_p)), datamod_rng_p[:, 1], datamod_rng_p[:, 0]], dtype=ret_dtype) - - ellipse_data_arr = ellipse_model(datamod_slim, ellipse_y_arr, np.asarray(datamod_rng_p[:, 4])).transpose((1, 0)) + [ + datamod_rng_p[:, 2], + datamod_rng_p[:, 3], + np.ones(len(datamod_rng_p)), + datamod_rng_p[:, 1], + datamod_rng_p[:, 0], + ], + dtype=ret_dtype, + ) + + ellipse_data_arr = ellipse_model( + datamod_slim, ellipse_y_arr, np.asarray(datamod_rng_p[:, 4]) + ).transpose((1, 0)) ellipse_data_abs = np.abs(ellipse_data_arr) ellipse_data_index = np.argmax(np.sum(ellipse_data_abs < offset, axis=1), axis=0) effective_data_arr = ellipse_data_arr[ellipse_data_index] effective_sample_p_arr = datamod_rng_p[ellipse_data_index] - + return fit_rotated_ellipse(effective_data_arr, effective_sample_p_arr) @@ -130,30 +160,29 @@ def fit_rotated_ellipse(data, P): theta = 0.5 * np.arctan(b / (a - c), dtype=np.float64) theta_sin = np.sin(theta, dtype=np.float64) theta_cos = np.cos(theta, dtype=np.float64) - tc2 = theta_cos ** 2 - ts2 = theta_sin ** 2 + tc2 = theta_cos**2 + ts2 = theta_sin**2 b_tcs = b * theta_cos * theta_sin - + # Do the calculation only once - cxy = b ** 2 - 4 * a * c + cxy = b**2 - 4 * a * c cx = (2 * c * d - b * e) / cxy cy = (2 * a * e - b * d) / cxy - + # I just want to clear things up around here. - cu = a * cx ** 2 + b * cx * cy + c * cy ** 2 - f + cu = a * cx**2 + b * cx * cy + c * cy**2 - f cu_r = np.array([(a * tc2 + b_tcs + c * ts2), (a * ts2 - b_tcs + c * tc2)]) - if cu > 1: #negatives can get thrown which cause errors, just ignore them + if cu > 1: # negatives can get thrown which cause errors, just ignore them wh = np.sqrt(cu / cu_r) else: pass w, h = wh[0], wh[1] - + error_sum = np.sum(data) # print("fitting error = %.3f" % (error_sum)) - - return (cx, cy, w, h, theta) + return (cx, cy, w, h, theta) def get_center_noclamp(center_xy, radius): @@ -168,22 +197,52 @@ def get_center_noclamp(center_xy, radius): ransac_upper_y = center_y + max(20, radius) ransac_lower_y = center_y - max(20, radius) ransac_xy_offset = (ransac_lower_x, ransac_lower_y) - return center_x, center_y, upper_x, lower_x, upper_y, lower_y, ransac_lower_x, ransac_lower_y, ransac_upper_x, ransac_upper_y, ransac_xy_offset + return ( + center_x, + center_y, + upper_x, + lower_x, + upper_y, + lower_y, + ransac_lower_x, + ransac_lower_y, + ransac_upper_x, + ransac_upper_y, + ransac_xy_offset, + ) cct = 300 + def RANSAC3D(self, hsrac_en): f = False ranf = False blink = 0.7 - if hsrac_en: - center_x, center_y, upper_x, lower_x, upper_y, lower_y, ransac_lower_x, ransac_lower_y, ransac_upper_x, ransac_upper_y, ransac_xy_offset = get_center_noclamp( - (self.rawx, self.rawy), self.radius) + ( + center_x, + center_y, + upper_x, + lower_x, + upper_y, + lower_y, + ransac_lower_x, + ransac_lower_y, + ransac_upper_x, + ransac_upper_y, + ransac_xy_offset, + ) = get_center_noclamp((self.rawx, self.rawy), self.radius) - frame = safe_crop(self.current_image_gray_clean, ransac_lower_x, ransac_lower_y, ransac_upper_x, ransac_upper_y, 1) + frame = safe_crop( + self.current_image_gray_clean, + ransac_lower_x, + ransac_lower_y, + ransac_upper_x, + ransac_upper_y, + 1, + ) else: frame = self.current_image_gray_clean @@ -201,29 +260,26 @@ def RANSAC3D(self, hsrac_en): # crop the image earlier; it gives us less possible dark area to get confused about in the # next step. - - # Crop first to reduce the amount of data to process. - # frame = self.current_image_gray + # frame = self.current_image_gray # For measuring processing time of image processing # Crop first to reduce the amount of data to process. # frame = frame[0:len(frame) - 5, :] # To reduce the processing data, blur. frame_gray = cv2.GaussianBlur(frame, (5, 5), 0) - # this will need to be adjusted everytime hardware is changed (brightness of IR, Camera postion, etc)m min_val, max_val, min_loc, max_loc = cv2.minMaxLoc(frame_gray) - + maxloc0_hf, maxloc1_hf = int(0.5 * max_loc[0]), int(0.5 * max_loc[1]) - + # crop 15% sqare around min_loc # frame_gray = frame_gray[max_loc[1] - maxloc1_hf:max_loc[1] + maxloc1_hf, - # max_loc[0] - maxloc0_hf:max_loc[0] + maxloc0_hf] + # max_loc[0] - maxloc0_hf:max_loc[0] + maxloc0_hf] if self.settings.gui_legacy_ransac: if self.eye_id in [EyeId.LEFT]: - threshold_value = self.settings.gui_legacy_ransac_thresh_left + threshold_value = self.settings.gui_legacy_ransac_thresh_left else: threshold_value = self.settings.gui_legacy_ransac_thresh_right else: @@ -248,7 +304,7 @@ def RANSAC3D(self, hsrac_en): # If empty, go to next loop pass try: - + cnt = sorted(hull, key=cv2.contourArea) maxcnt = cnt[-1] # ellipse = cv2.fitEllipse(maxcnt) @@ -260,31 +316,31 @@ def RANSAC3D(self, hsrac_en): cx, cy, w, h, theta = ransac_data # print(cx, cy) - #cxi, cyi, wi, hi = int(cx), int(cy), int(w), int(h) - - #cv2.drawContours(self.current_image_gray, contours, -1, (255, 0, 0), 1) - # cv2.circle(self.current_image_gray, (cx, cy), 2, (0, 0, 255), -1) - # cx1, cy1, w1, h1, theta1 = fit_rotated_ellipse(maxcnt.reshape(-1, 2)) - # cv2.ellipse(self.current_image_gray, (cx, cy), (w, h), theta * 180.0 / np.pi, 0.0, 360.0, (50, 250, 200), 1, ) + # cxi, cyi, wi, hi = int(cx), int(cy), int(w), int(h) - #img = newImage2[y1:y2, x1:x2] + # cv2.drawContours(self.current_image_gray, contours, -1, (255, 0, 0), 1) + # cv2.circle(self.current_image_gray, (cx, cy), 2, (0, 0, 255), -1) + # cx1, cy1, w1, h1, theta1 = fit_rotated_ellipse(maxcnt.reshape(-1, 2)) + # cv2.ellipse(self.current_image_gray, (cx, cy), (w, h), theta * 180.0 / np.pi, 0.0, 360.0, (50, 250, 200), 1, ) + + # img = newImage2[y1:y2, x1:x2] except: ranf = True pass self.current_image_gray = frame - cv2.circle(self.current_image_gray, min_loc, 2, (0, 0, 255), - -1) # the point of the darkest area in the image - + cv2.circle( + self.current_image_gray, min_loc, 2, (0, 0, 255), -1 + ) # the point of the darkest area in the image # However eyes are annoyingly three dimensional, so we need to take this ellipse and turn it # into a curve patch on the surface of a sphere (the eye itself). If it's not a sphere, see your # ophthalmologist about possible issues with astigmatism. try: - # Get axis and angle of the ellipse, using pupil labs 2d algos. The next bit of code ranges - # from somewhat to completely magic, as most of it happens in native libraries (hence passing - # via dicts). + # Get axis and angle of the ellipse, using pupil labs 2d algos. The next bit of code ranges + # from somewhat to completely magic, as most of it happens in native libraries (hence passing + # via dicts). result_2d = {} result_2d_final = {} result_2d["center"] = (cx, cy) @@ -297,11 +353,11 @@ def RANSAC3D(self, hsrac_en): result_2d_final["timestamp"] = self.current_frame_number / self.current_fps # Black magic happens here, but after this we have our reprojected pupil/eye, and all we had # to do was sell our soul to satan and/or C++. - + result_3d = self.detector_3d.update_and_detect( result_2d_final, self.current_image_gray ) - + # Now we have our pupil ellipse_3d = result_3d["ellipse"] # And our eyeball that the pupil is on the surface of @@ -323,88 +379,86 @@ def RANSAC3D(self, hsrac_en): csx = newFrame2.shape[1] if hsrac_en: - if ranf: cx = self.rawx cy = self.rawy else: - # print(int(cx), int(clamp(cx + ransac_lower_x, 0, csx)), ransac_lower_x, csx, "y", int(cy), int(clamp(cy + ransac_lower_y, 0, csy)), ransac_lower_y, csy) - cx = int(clamp(cx + ransac_lower_x, 0, csx)) #dunno why this is being weird + # print(int(cx), int(clamp(cx + ransac_lower_x, 0, csx)), ransac_lower_x, csx, "y", int(cy), int(clamp(cy + ransac_lower_y, 0, csy)), ransac_lower_y, csy) + cx = int( + clamp(cx + ransac_lower_x, 0, csx) + ) # dunno why this is being weird cy = int(clamp(cy + ransac_lower_y, 0, csy)) - - #print(contours) + # print(contours) for cnt in contours: (x, y, w, h) = cv2.boundingRect(cnt) perscalarw = w / csx perscalarh = h / csy - # print(abs(perscalarw-perscalarh)) - # if abs(perscalarw-perscalarh) >= 0.2: # TODO setting + # print(abs(perscalarw-perscalarh)) + # if abs(perscalarw-perscalarh) >= 0.2: # TODO setting # blink = 0.0 if self.settings.gui_RANSACBLINK: if self.ran_blink_check_for_file: if self.eye_id in [EyeId.LEFT]: - file_path = 'RANSAC_blink_LEFT.cfg' + file_path = "RANSAC_blink_LEFT.cfg" if self.eye_id in [EyeId.RIGHT]: - file_path = 'RANSAC_blink_RIGHT.cfg' + file_path = "RANSAC_blink_RIGHT.cfg" else: - file_path = 'RANSAC_blink_RIGHT.cfg' + file_path = "RANSAC_blink_RIGHT.cfg" if os.path.exists(file_path): - with open(file_path, 'r') as file: + with open(file_path, "r") as file: self.blink_list = [float(line.strip()) for line in file] else: - print(f"\033[93m[INFO] RANSAC Blink Config '{file_path}' not found. Waiting for calibration.\033[0m") + print( + f"\033[93m[INFO] RANSAC Blink Config '{file_path}' not found. Waiting for calibration.\033[0m" + ) self.ran_blink_check_for_file = False - - if len(self.blink_list) == 10000: # self calibrate ransac blink IN TESTING + if len(self.blink_list) == 10000: # self calibrate ransac blink IN TESTING if self.eye_id in [EyeId.LEFT]: - with open("RANSAC_BLINK_LEFT.cfg", 'w') as file: + with open("RANSAC_BLINK_LEFT.cfg", "w") as file: for item in self.blink_list: - file.write(str(item) + '\n') + file.write(str(item) + "\n") if self.eye_id in [EyeId.RIGHT]: - with open("RANSAC_BLINK_RIGHT.cfg", 'w') as file: + with open("RANSAC_BLINK_RIGHT.cfg", "w") as file: for item in self.blink_list: - file.write(str(item) + '\n') - print('SAVE') + file.write(str(item) + "\n") + print("SAVE") - # self.blink_list.pop(0) - self.blink_list.append(abs(perscalarw-perscalarh)) + # self.blink_list.pop(0) + self.blink_list.append(abs(perscalarw - perscalarh)) elif len(self.blink_list) < 10000: - self.blink_list.append(abs(perscalarw-perscalarh)) + self.blink_list.append(abs(perscalarw - perscalarh)) - - if abs(perscalarw-perscalarh) >= np.percentile( - self.blink_list, 94 - ): + if abs(perscalarw - perscalarh) >= np.percentile(self.blink_list, 94): blink = 0.0 - - try: - cv2.drawContours(self.current_image_gray, contours, -1, (255, 0, 0), 1) # TODO: fix visualizations with HSRAC + cv2.drawContours( + self.current_image_gray, contours, -1, (255, 0, 0), 1 + ) # TODO: fix visualizations with HSRAC cv2.circle(self.current_image_gray, (int(cx), int(cy)), 2, (0, 0, 255), -1) except: pass # try: #for some reason the pye3d visualizations are wack, im going to just not visualize it for now.. - # cv2.ellipse( - # self.current_image_gray, - # tuple(int(v) for v in ellipse_3d["center"]), - # tuple(int(v) for v in ellipse_3d["axes"]), - # ellipse_3d["angle"], - # 0, - # 360, # start/end angle for drawing - # (0, 255, 0), # color (BGR): red - # ) + # cv2.ellipse( + # self.current_image_gray, + # tuple(int(v) for v in ellipse_3d["center"]), + # tuple(int(v) for v in ellipse_3d["axes"]), + # ellipse_3d["angle"], + # 0, + # 360, # start/end angle for drawing + # (0, 255, 0), # color (BGR): red + # ) # except Exception: - # Sometimes we get bogus axes and trying to draw this throws. Ideally we should check for - # validity beforehand, but for now just pass. It usually fixes itself on the next frame. + # Sometimes we get bogus axes and trying to draw this throws. Ideally we should check for + # validity beforehand, but for now just pass. It usually fixes itself on the next frame. # pass try: @@ -421,23 +475,21 @@ def RANSAC3D(self, hsrac_en): # draw line from center of eyeball to center of pupil # cv2.line( - # self.current_image_gray, + # self.current_image_gray, # tuple(int(v) for v in self.lkg_projected_sphere["center"]), - # tuple(int(v) for v in ellipse_3d["center"]), - # (0, 255, 0), # color (BGR): red + # tuple(int(v) for v in ellipse_3d["center"]), + # (0, 255, 0), # color (BGR): red # ) except: pass - - self.current_image_gray = newFrame2 y, x = self.current_image_gray.shape - thresh = cv2.resize(thresh, (x,y)) - try: - self.failed = 0 # we have succeded, continue with this + thresh = cv2.resize(thresh, (x, y)) + try: + self.failed = 0 # we have succeded, continue with this return cx, cy, thresh, blink except: - self.failed = self.failed + 1 #we have failed, move onto next algo - return 0, 0, thresh, blink \ No newline at end of file + self.failed = self.failed + 1 # we have failed, move onto next algo + return 0, 0, thresh, blink