forked from jgrewe/efish_tracking
185 lines
6.8 KiB
Python
185 lines
6.8 KiB
Python
from cv2 import calibrationMatrixValues
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import matplotlib.pyplot as plt
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import numpy as np
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import cv2
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import os
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import sys
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from IPython import embed
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class DistanceCalibration:
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def __init__(self, file_name, x_0=95, y_0=185, cam_dist=1.36, width=1.35, height=0.805, width_pixel=1975, height_pixel=1375, checkerboard_width=0.24, checkerboard_height=0.18,
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checkerboard_width_pixel=500, checkerboard_height_pixel=350, rectangle_width=0.024, rectangle_height=0.0225, rectangle_width_pixel=100, rectangle_height_pixel=90,
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rectangle_count_width=9, rectangle_count_height=7) -> None:
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# aktualisieren
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"""Calibration of the dimensions of the tank. Conversion of pixel into meter. Width refers to the "x-axis", height to the "y-axis" of the tank.
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Args:
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file_name (_type_): _description_
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x_0 (int, optional): X-value of the "origin" of the tank. Defaults to 0.
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y_0 (int, optional): Y-value of the "origin" of the tank. Defaults to 0.
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cam_dist (int, optional): Distance of camera lense to tank floor. Defaults to 1.36.
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width (int, optional): Width in meter from one lightened corner of the tank to the other. Defaults to 1.35.
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heigth (int, optional): Height in meter from one lightened corner of the tank to the other. Defaults to 1.35.
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width_pixel (int, optional): Width in pixel from one lightened corner of the tank to the other. Defaults to 1975.
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height_pixel (int, optional): Heigth in pixel from one lightened corner of the tank to the other. Defaults to 1375.
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rectangle_width (float, optional): Width of one black or corresponding white rectangle of the checkerboard. Defaults to 0.024.
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rectangle_height (float, optional): Height of one black or corresponding white rectangle of the checkerboard. Defaults to 0.0225.
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rectangle_count_width (int, optional): Number of black rectangles over the width of the whole checkerboard. Defaults to 9.
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rectangle_count_height (int, optional): Number of black rectangles over the height of the whole checkerboard. Defaults to 7.
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"""
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self._file_name = file_name
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self._x_0 = x_0
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self._y_0 = y_0
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self._width_pix = width_pixel
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self._height_pix = height_pixel
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self._cam_dist = cam_dist
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self._width = width
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self._height = height
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self._cb_width = checkerboard_width
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self._cb_height = checkerboard_height
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self._cb_width_pix = checkerboard_width_pixel
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self._cb_height_pix = checkerboard_height_pixel
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self._rect_width = rectangle_width
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self._rect_height = rectangle_height
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self._x_factor = self.width / self.width_pix # m/pix
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self._y_factor = self.height / self.height_pix # m/pix
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# properties
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@property
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def x_0(self):
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return self._x_0
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@property
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def y_0(self):
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return self._y_0
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@property
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def cam_dist(self):
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return self._cam_dist
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@property
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def width(self):
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return self._width
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@property
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def height(self):
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return self._height
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@property
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def width_pix(self):
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return self._width_pix
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@property
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def height_pix(self):
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return self._height_pix
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@property
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def x_factor(self):
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return self._x_factor
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@property
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def y_factor(self):
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return self._y_factor
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def crop_movie():
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if not os.path.exists(filename):
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raise IOError("file %s does not exist!" % filename)
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video = cv2.VideoCapture()
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video.open(filename)
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frame_counter = 0
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success = True
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frame = None
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while success and frame_counter <= frame_number: # iterating until frame_counter == frame_number --> success (True)
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print("Reading frame: %i" % frame_counter, end="\r")
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success, frame = video.read()
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frame_counter += 1
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if success:
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self._fig.gca().imshow(frame) # plot wanted frame of video
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else:
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print("Could not read frame number %i either failed to open movie or beyond maximum frame number!" % frame_number)
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return []
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plt.ion() # turn on interactive mode
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plt.show(block=False) # block=False allows to continue interact in terminal while the figure is open
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self._task_index = -1
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if len(self._tasks) > 0:
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self._next_task()
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while not self._tasks_done:
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plt.pause(0.250)
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if self._interrupt:
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return []
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self._fig.gca().set_title("All set and done!\n Window will close in 2s")
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self._fig.canvas.draw()
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plt.pause(2.0)
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plt.close()
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return [t.marker_positions for t in self._tasks]
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def mark_checkerboard(self, filename, frame_number=10):
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if not os.path.exists(filename):
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raise IOError("file %s does not exist!" % filename)
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video = cv2.VideoCapture()
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video.open(filename)
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frame_counter = 0
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success = True
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frame = None
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x_0 = self._x_0
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y_0 = self._y_0
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width_pix = self._width_pix
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height_pix = self._height_pix
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while success and frame_counter <= frame_number: # iterating until frame_counter == frame_number --> success (True)
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print("Reading frame: %i" % frame_counter, end="\r")
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success, frame = video.read()
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frame_counter += 1
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width_mean = np.mean(frame,axis=1)
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crop_width_mean = width_mean[x_0:width_pix]
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height_mean = np.mean(frame,axis=0)
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crop_height_mean = height_mean[y_0:height_pix]
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# HELLO, here you at
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embed()
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quit()
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if success:
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self._fig.gca().imshow(frame) # plot wanted frame of video
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else:
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print("Could not read frame number %i either failed to open movie or beyond maximum frame number!" % frame_number)
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return []
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plt.ion() # turn on interactive mode
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plt.show(block=False) # block=False allows to continue interact in terminal while the figure is open
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self._task_index = -1
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if len(self._tasks) > 0:
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self._next_task()
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while not self._tasks_done:
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plt.pause(0.250)
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if self._interrupt:
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return []
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self._fig.gca().set_title("All set and done!\n Window will close in 2s")
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self._fig.canvas.draw()
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plt.pause(2.0)
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plt.close()
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return [t.marker_positions for t in self._tasks]
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if __name__ == "__main__":
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vid2 = "/home/efish/etrack/videos/2022.03.28_3.mp4"
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calibration_task = DistanceCalibration(vid2)
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dc = DistanceCalibration(calibration_task)
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dc.mark_checkerboard(vid2, 10)
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# print(sys.argv[0])
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# print (sys.argv[1])
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# vid1 = sys.argv[1]
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embed() |