use qt gui instead of opencv
parent
f26f958dc7
commit
9c1115d505
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@ -4,6 +4,9 @@ import cv2
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import os
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import time
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import math
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from pyqtgraph.Qt import QtCore, QtGui
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import pyqtgraph as pg
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from shapely.geometry import LineString
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from queue import Queue
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@ -26,7 +29,25 @@ class ArucoEstimator:
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'd': {'pixel_coordinate': None, 'x': None, 'y': None, 'n_estimates': 0},
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}
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def __init__(self, robot_marker_ids=None, use_realsense=True, grid_columns=8, grid_rows=8):
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def __init__(self, robot_marker_ids=None, use_realsense=True, grid_columns=12, grid_rows=12):
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self.app = QtGui.QApplication([])
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## Create window with GraphicsView widget
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self.win = pg.GraphicsLayoutWidget()
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self.win.keyPressEvent = self.handleKeyPressEvent
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self.win.show() ## show widget alone in its own window
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self.win.setWindowTitle('ArucoEstimator')
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self.view = self.win.addViewBox()
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## lock the aspect ratio so pixels are always square
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self.view.setAspectLocked(True)
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## Create image item
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self.img = pg.ImageItem(border='w')
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self.img.setLevels([[0, 255], [0, 255], [0, 255]])
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self.img.mouseClickEvent = self.handleMouseEvent
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self.view.addItem(self.img)
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self.grid_columns = grid_columns
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self.grid_rows = grid_rows
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@ -38,6 +59,9 @@ class ArucoEstimator:
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self.draw_grid = False
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self.fps_start_time = time.time()
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self.fps_counter = 0
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self.event_queue = Queue()
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if use_realsense: # check if realsense camera is connected
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@ -89,6 +113,7 @@ class ArucoEstimator:
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self.drag_line_end = None
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self.drag_line_start = None
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self.previous_click = None
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self.invert_grayscale = False
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def compute_clicked_position(self, px, py):
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if self.all_corners_detected():
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@ -116,21 +141,16 @@ class ArucoEstimator:
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target = np.array([px, -py])
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return target
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def mouse_callback(self, event, px, py, flags, param):
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"""
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This function is called for each mouse event inside the opencv window.
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If there are reference markers available we compute the real world position corresponding to the clicked
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position and put it in an event queue.
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:param event: type of event (mouse movement, left click, right click, etc.)
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:param px: x-position of event
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:param py: y-position of event
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"""
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target = None
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if event == cv2.EVENT_LBUTTONDOWN:
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self.drag_line_start = (px, py)
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elif event == cv2.EVENT_LBUTTONUP:
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def handleMouseEvent(self, event):
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# get click position as distance to top-left corner of the image
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px = event.pos().x()
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py = self.img.height() - event.pos().y()
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print(f"px = {px}, py = {py}")
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if event.button() == QtCore.Qt.MouseButton.LeftButton:
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# self.drag_line_start = (px, py)
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# elif event == cv2.EVENT_LBUTTONUP:
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self.drag_line_end = (px, py)
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self.drag_line_start = (px, py)
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target_pos = self.compute_clicked_position(self.drag_line_start[0], self.drag_line_start[1])
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if self.drag_line_start != self.drag_line_end:
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# compute target angle for clicked position
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@ -155,106 +175,99 @@ class ArucoEstimator:
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if self.drag_line_start is not None:
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self.drag_line_end = (px, py)
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def run_tracking(self, draw_markers=True, draw_marker_coordinate_system=False, invert_grayscale=False):
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"""
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Run the marker tracking in a loop
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"""
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cv2.namedWindow('RoboRally', cv2.WINDOW_AUTOSIZE)
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cv2.setMouseCallback('RoboRally', self.mouse_callback)
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def process_frame(self):
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draw_markers=True
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draw_marker_coordinate_system=False
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#cv2.setMouseCallback('RoboRally', self.mouse_callback)
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fps_display_rate = 1 # displays the frame rate every 1 second
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fps_counter = 0
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start_time = time.time()
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try:
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running = True
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while running:
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if self.pipeline:
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frames = self.pipeline.wait_for_frames()
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color_frame = frames.get_color_frame()
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if not color_frame:
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continue
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# Convert images to numpy arrays
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color_image = np.asanyarray(color_frame.get_data())
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if self.pipeline:
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frames = self.pipeline.wait_for_frames()
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color_frame = frames.get_color_frame()
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# if not color_frame:
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# continue
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# Convert images to numpy arrays
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color_image = np.asanyarray(color_frame.get_data())
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else:
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# Capture frame-by-frame
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ret, color_image = self.cv_camera.read()
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t_image = time.time()
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gray = cv2.cvtColor(color_image, cv2.COLOR_BGR2GRAY)
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if self.invert_grayscale:
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cv2.bitwise_not(gray, gray)
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# run aruco marker detection
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detected_markers = self.detector.detect(gray)
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# extract data for detected markers
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detected_marker_data = {}
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for marker in detected_markers:
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if marker.id >= 0:
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detected_marker_data[marker.id] = {'marker_center': marker.getCenter()}
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if marker.id in self.corner_marker_ids.values():
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marker.calculateExtrinsics(0.075, self.camparam)
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else:
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# Capture frame-by-frame
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ret, color_image = self.cv_camera.read()
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t_image = time.time()
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marker.calculateExtrinsics(0.07, self.camparam)
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detected_marker_data[marker.id]['Rvec'] = marker.Rvec
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detected_marker_data[marker.id]['Tvec'] = marker.Tvec
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gray = cv2.cvtColor(color_image, cv2.COLOR_BGR2GRAY)
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if invert_grayscale:
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cv2.bitwise_not(gray, gray)
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if draw_markers:
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marker.draw(color_image, np.array([255, 255, 255]), 2, True)
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# run aruco marker detection
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detected_markers = self.detector.detect(gray)
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if draw_marker_coordinate_system:
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aruco.CvDrawingUtils.draw3dAxis(color_image, self.camparam, marker.Rvec, marker.Tvec, .1)
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# extract data for detected markers
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detected_marker_data = {}
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for marker in detected_markers:
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if marker.id >= 0:
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detected_marker_data[marker.id] = {'marker_center': marker.getCenter()}
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# store data
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for marker_id, data in detected_marker_data.items():
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self.update_estimate(marker_id, data['marker_center'], data['Rvec'], data['Tvec'], t_image)
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if marker.id in self.corner_marker_ids.values():
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marker.calculateExtrinsics(0.075, self.camparam)
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else:
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marker.calculateExtrinsics(0.07, self.camparam)
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detected_marker_data[marker.id]['Rvec'] = marker.Rvec
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detected_marker_data[marker.id]['Tvec'] = marker.Tvec
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# draw grid
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if self.draw_grid:
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color_image = self.draw_grid_lines(color_image, detected_marker_data)
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color_image = self.draw_robot_pos(color_image, detected_marker_data)
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if draw_markers:
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marker.draw(color_image, np.array([255, 255, 255]), 2, True)
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# draw drag
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if self.drag_line_start is not None and self.drag_line_end is not None:
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color_image = cv2.line(color_image, self.drag_line_start, self.drag_line_end, color=(0, 0, 255), thickness=2)
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if draw_marker_coordinate_system:
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aruco.CvDrawingUtils.draw3dAxis(color_image, self.camparam, marker.Rvec, marker.Tvec, .1)
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# compute frame rate
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self.fps_counter += 1
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delta_t = time.time() - self.fps_start_time
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if delta_t > fps_display_rate:
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self.fps_counter = 0
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self.fps_start_time = time.time()
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color_image = cv2.putText(color_image, f"fps = {(self.fps_counter / delta_t):.2f}", (10, 25), cv2.FONT_HERSHEY_PLAIN, 2,
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(0, 255, 255),
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thickness=2)
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# store data
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for marker_id, data in detected_marker_data.items():
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self.update_estimate(marker_id, data['marker_center'], data['Rvec'], data['Tvec'], t_image)
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# Show images
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color_image_rgb = cv2.cvtColor(color_image, cv2.COLOR_BGR2RGB) # convert to RGB
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self.img.setImage(np.transpose(np.flipud(color_image_rgb), axes=(1, 0, 2)))
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# draw grid
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if self.draw_grid:
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color_image = self.draw_grid_lines(color_image, detected_marker_data)
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color_image = self.draw_robot_pos(color_image, detected_marker_data)
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QtCore.QTimer.singleShot(1, self.process_frame)
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# draw drag
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if self.drag_line_start is not None and self.drag_line_end is not None:
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color_image = cv2.line(color_image, self.drag_line_start, self.drag_line_end, color=(0, 0, 255), thickness=2)
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# compute frame rate
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fps_counter += 1
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delta_t = time.time() - start_time
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if delta_t > fps_display_rate:
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fps_counter = 0
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start_time = time.time()
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color_image = cv2.putText(color_image, f"fps = {(fps_counter / delta_t):.2f}", (10, 25), cv2.FONT_HERSHEY_PLAIN, 2,
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(0, 255, 255),
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thickness=2)
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# Show images
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cv2.imshow('RoboRally', color_image)
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key = cv2.waitKey(1)
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if key > 0:
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self.event_queue.put(('key', key))
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if key == ord('g'):
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self.draw_grid = not self.draw_grid
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if key == ord('q'):
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running = False
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if key == ord('x'):
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color_sensor = self.pipeline.get_active_profile().get_device().query_sensors()[1]
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if color_sensor.get_option(rs.option.enable_auto_exposure) == 1.0:
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color_sensor.set_option(rs.option.enable_auto_exposure, False)
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print("auto exposure OFF")
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else:
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color_sensor.set_option(rs.option.enable_auto_exposure, True)
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print("auto exposure ON")
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if key == ord('i'):
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invert_grayscale = not invert_grayscale
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finally:
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cv2.destroyAllWindows()
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def handleKeyPressEvent(self, ev):
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key = ev.key()
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self.event_queue.put(('key', key))
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if key == QtCore.Qt.Key_G:
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self.draw_grid = not self.draw_grid
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elif key == QtCore.Qt.Key_Q:
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if self.pipeline is not None:
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# Stop streaming
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self.pipeline.stop()
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self.app.quit()
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elif key == QtCore.Qt.Key_X:
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if self.pipeline is not None:
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color_sensor = self.pipeline.get_active_profile().get_device().query_sensors()[1]
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if color_sensor.get_option(rs.option.enable_auto_exposure) == 1.0:
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color_sensor.set_option(rs.option.enable_auto_exposure, False)
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print("auto exposure OFF")
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else:
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color_sensor.set_option(rs.option.enable_auto_exposure, True)
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print("auto exposure ON")
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elif key == QtCore.Qt.Key_I:
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self.invert_grayscale = not self.invert_grayscale
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def update_estimate(self, marker_id, pixel_coord_center, rvec, tvec, t_image):
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# update the marker estimate with new data
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if marker_id in self.corner_marker_ids.values():
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@ -445,5 +458,12 @@ class ArucoEstimator:
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if __name__ == "__main__":
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estimator = ArucoEstimator(use_realsense=True, robot_marker_ids=[11, 12, 13, 14])
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estimator.run_tracking(draw_markers=True, invert_grayscale=True)
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estimator = ArucoEstimator(use_realsense=False, robot_marker_ids=[11, 12, 13, 14])
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estimator.process_frame()
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import sys
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if (sys.flags.interactive != 1) or not hasattr(QtCore, 'PYQT_VERSION'):
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QtGui.QApplication.instance().exec_()
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#estimator.run_tracking(draw_markers=True, invert_grayscale=True)
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@ -0,0 +1,62 @@
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import socket
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import pygame
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from argparse import ArgumentParser
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class ManualController:
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def __init__(self, estimator):
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self.estimator = estimator
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self.estimator.external_keyboard_callback = self.handle_keypress
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self.controlling = False
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def handle_keypress(self, key):
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pass
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parser = ArgumentParser()
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parser.add_argument('ip', metavar='ip', type=str, help='ip address of the controlled robot')
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args = parser.parse_args()
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ip = args.ip
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pygame.init()
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pygame.display.set_mode((640, 480))
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rc_socket = socket.socket()
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try:
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rc_socket.connect((ip, 1234)) # connect to robot
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except socket.error:
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print("could not connect to socket")
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running = True
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while running:
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u1 = 0
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u2 = 0
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vmax = 1.0
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events = pygame.event.get()
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for event in events:
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if event.type == pygame.KEYDOWN:
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if event.key == pygame.K_LEFT:
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u1 = -vmax
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u2 = vmax
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print(f"turn left: ({u1},{u2})")
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elif event.key == pygame.K_RIGHT:
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u1 = vmax
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u2 = -vmax
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print(f"turn right: ({u1},{u2})")
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elif event.key == pygame.K_UP:
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u1 = vmax
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u2 = vmax
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print(f"forward: ({u1},{u2})")
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elif event.key == pygame.K_DOWN:
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u1 = -vmax
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u2 = -vmax
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print(f"backward: ({u1},{u2})")
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elif event.key == pygame.K_ESCAPE:
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print("quit")
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running = False
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u1 = 0.0
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u2 = 0.0
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rc_socket.send(f'({u1},{u2})\n'.encode())
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elif event.type == pygame.KEYUP:
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print("key released, resetting: ({},{})".format(u1, u2))
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rc_socket.send(f'({u1},{u2})\n'.encode())
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@ -0,0 +1,117 @@
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from flask import Flask, render_template, request
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import socket
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import threading
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import time
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import numpy as np
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from robot import Robot
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from mpc_controller import MPCController
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from aruco_estimator import ArucoEstimator
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from shapely.geometry import LineString
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width = 600
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height = 400
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robot_ids = [11, 12, 13, 14]
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robot_ids_control_history = [11, 12, 13, 14]
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app = Flask(__name__)
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def calc_target_pos(px, py):
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if rc.estimator.all_corners_detected():
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# compute column line
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a = np.array([rc.estimator.corner_estimates['a']['x'], rc.estimator.corner_estimates['a']['y']])
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b = np.array([rc.estimator.corner_estimates['b']['x'], rc.estimator.corner_estimates['b']['y']])
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c = np.array([rc.estimator.corner_estimates['c']['x'], rc.estimator.corner_estimates['c']['y']])
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d = np.array([rc.estimator.corner_estimates['d']['x'], rc.estimator.corner_estimates['d']['y']])
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x_frac = (px + 0.5) / width
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y_frac = (py + 0.5) / height
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vab = b - a
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vdc = c - d
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column_line_top = a + x_frac * vab
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column_line_bottom = d + x_frac * vdc
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vad = d - a
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vbc = c - b
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row_line_top = a + y_frac * vad
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row_line_bottom = b + y_frac * vbc
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column_line = LineString([column_line_top, column_line_bottom])
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row_line = LineString([row_line_top, row_line_bottom])
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int_pt = column_line.intersection(row_line)
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point_of_intersection = np.array([int_pt.x, int_pt.y, 0.0])
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return point_of_intersection
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@app.route('/', methods=('GET', 'POST'))
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def presence():
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global robot_ids_control_history
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if request.method == 'GET':
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return render_template('telepresence.html', oldest_control=robot_ids.index(robot_ids_control_history[0]))
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elif request.method == 'POST':
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x = int(float(request.form.get('x')))
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y = int(float(request.form.get('y')))
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print(x, y)
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margin = 0.1
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x = min(max(width * margin, x), width * (1 - margin))
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y = min(max(height * margin, y), height * (1 - margin))
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id = int(request.form.get('robot'))
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robot_ids_control_history.append(robot_ids_control_history.pop(robot_ids_control_history.index(id)))
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target_pos = calc_target_pos(x, y)
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rc.estimator.event_queue.put(('robot', id, target_pos))
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return 'OK'
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class RemoteController:
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def __init__(self):
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self.robots = []
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#self.robots = [Robot(11, '192.168.1.11')] #, Robot(13, '192.168.1.13'), Robot(14, '192.168.1.14')]
|
||||
self.robots = [Robot(11, '10.10.11.88'), Robot(12, '10.10.11.91'),
|
||||
Robot(13, '10.10.11.90'), Robot(14, '10.10.11.89')]
|
||||
|
||||
self.robot_ids = {}
|
||||
for r in self.robots:
|
||||
self.robot_ids[r.id] = r
|
||||
|
||||
# socket for movement commands
|
||||
self.comm_socket = socket.socket()
|
||||
self.comm_socket.setsockopt(socket.SOL_SOCKET, socket.SO_REUSEADDR, 1)
|
||||
|
||||
for robot in self.robots:
|
||||
robot.connect()
|
||||
|
||||
self.comm_socket.bind(('', 1337))
|
||||
self.comm_socket.listen(5)
|
||||
|
||||
self.t = time.time()
|
||||
|
||||
# start thread for marker position detection
|
||||
self.estimator = ArucoEstimator(self.robot_ids.keys())
|
||||
self.estimator_thread = threading.Thread(target=self.estimator.run_tracking, kwargs={'draw_markers':False})
|
||||
self.estimator_thread.start()
|
||||
|
||||
self.controller = MPCController(self.estimator)
|
||||
|
||||
def run(self):
|
||||
print("waiting until all markers are detected...")
|
||||
while not (self.estimator.all_corners_detected() and self.estimator.all_robots_detected()):
|
||||
pass
|
||||
print("starting control")
|
||||
self.controller.interactive_control(robots=self.robots)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
rc = RemoteController()
|
||||
rc_thread = threading.Thread(target=rc.run)
|
||||
rc_thread.start()
|
||||
|
||||
app.run('0.0.0.0')
|
||||
|
|
@ -0,0 +1,85 @@
|
|||
<!DOCTYPE html>
|
||||
<html lang="en">
|
||||
<head>
|
||||
<meta charset="UTF-8">
|
||||
<title>Mensa-Abend Telepräsenz</title>
|
||||
<style>
|
||||
div.meerschweinchen {
|
||||
max-width: 600px;
|
||||
margin: auto;
|
||||
text-align: center;
|
||||
}
|
||||
div.arena {
|
||||
height: 400px;
|
||||
width: 600px;
|
||||
background-image: url("https://p.0au.de/3d62ea7/foo.png");
|
||||
border: none;
|
||||
text-align: center;
|
||||
position: relative
|
||||
}
|
||||
div.arena p {
|
||||
margin: 0;
|
||||
position: absolute;
|
||||
top: 50%;
|
||||
left: 50%;
|
||||
transform: translate(-50%, -50%)
|
||||
}
|
||||
</style>
|
||||
|
||||
<script type=text/javascript src="{{url_for('static', filename='jquery-3.5.1.min.js') }}"></script>
|
||||
</head>
|
||||
<body>
|
||||
<h1 style="text-align: center">Welcome to Mensa-Abend digital</h1>
|
||||
<div style="text-align: center">
|
||||
<p>Click anywhere to control the robots in our hackerspace. You can see them in the Zoom video.<br>
|
||||
<br>
|
||||
Please let us know about your study background.
|
||||
</p>
|
||||
</div>
|
||||
<div class="meerschweinchen">
|
||||
<div class=arena style="font-size: large;">
|
||||
|
||||
</div>
|
||||
|
||||
<form method="post">
|
||||
<p>Choose your robot:</p>
|
||||
<div>
|
||||
<input type="radio" id="r11" name="robot_id" value="11">
|
||||
<label for="r11">Robot 11</label>
|
||||
</div>
|
||||
<div>
|
||||
<input type="radio" id="r12" name="robot_id" value="12">
|
||||
<label for="r12">Robot 12</label>
|
||||
</div>
|
||||
<div>
|
||||
<input type="radio" id="r13" name="robot_id" value="13">
|
||||
<label for="r13">Robot 13</label>
|
||||
</div>
|
||||
<div>
|
||||
<input type="radio" id="r14" name="robot_id" value="14">
|
||||
<label for="r14">Robot 14</label>
|
||||
</div>
|
||||
</form>
|
||||
</div>
|
||||
</body>
|
||||
|
||||
<script>
|
||||
function fireThis(e) {
|
||||
var parentOffset = $(this).parent().offset();
|
||||
var x = e.pageX - parentOffset.left;
|
||||
var y = e.pageY - parentOffset.top;
|
||||
|
||||
var robot = document.querySelector('input[name = "robot_id"]:checked').value;
|
||||
|
||||
$.post( "/", { 'x': x, 'y': y , 'robot': robot} );
|
||||
}
|
||||
|
||||
$('.arena').on('mousedown', fireThis);
|
||||
|
||||
function callRandom() {
|
||||
var array = document.getElementsByName('robot_id');
|
||||
array[{{ oldest_control }}].checked = true;
|
||||
}
|
||||
callRandom();
|
||||
</script>
|
||||
</html>
|
||||
Loading…
Reference in New Issue