use qt gui instead of opencv

remote_control/aruco_estimator.py

@@ -4,6 +4,9 @@ import cv2
 import os
 import time
 import math
+from pyqtgraph.Qt import QtCore, QtGui
+import pyqtgraph as pg
+
 
 from shapely.geometry import LineString
 from queue import Queue
@@ -26,7 +29,25 @@ class ArucoEstimator:
         'd': {'pixel_coordinate': None, 'x': None, 'y': None, 'n_estimates': 0},
     }
 
-    def __init__(self, robot_marker_ids=None, use_realsense=True, grid_columns=8, grid_rows=8):
+    def __init__(self, robot_marker_ids=None, use_realsense=True, grid_columns=12, grid_rows=12):
+        self.app = QtGui.QApplication([])
+
+        ## Create window with GraphicsView widget
+        self.win = pg.GraphicsLayoutWidget()
+        self.win.keyPressEvent = self.handleKeyPressEvent
+        self.win.show()  ## show widget alone in its own window
+        self.win.setWindowTitle('ArucoEstimator')
+        self.view = self.win.addViewBox()
+
+        ## lock the aspect ratio so pixels are always square
+        self.view.setAspectLocked(True)
+
+        ## Create image item
+        self.img = pg.ImageItem(border='w')
+        self.img.setLevels([[0, 255], [0, 255], [0, 255]])
+        self.img.mouseClickEvent = self.handleMouseEvent
+        self.view.addItem(self.img)
+
         self.grid_columns = grid_columns
         self.grid_rows = grid_rows
 
@@ -38,6 +59,9 @@ class ArucoEstimator:
 
         self.draw_grid = False
 
+        self.fps_start_time = time.time()
+        self.fps_counter = 0
+
         self.event_queue = Queue()
 
         if use_realsense:  # check if realsense camera is connected
@@ -89,6 +113,7 @@ class ArucoEstimator:
         self.drag_line_end = None
         self.drag_line_start = None
         self.previous_click = None
+        self.invert_grayscale = False
 
     def compute_clicked_position(self, px, py):
         if self.all_corners_detected():
@@ -116,21 +141,16 @@ class ArucoEstimator:
             target = np.array([px, -py])
         return target
 
-    def mouse_callback(self, event, px, py, flags, param):
-        """
-        This function is called for each mouse event inside the opencv window.
-        If there are reference markers available we compute the real world position corresponding to the clicked
-        position and put it in an event queue.
-        :param event: type of event (mouse movement, left click, right click, etc.)
-        :param px: x-position of event
-        :param py: y-position of event
-        """
-        target = None
-
-        if event == cv2.EVENT_LBUTTONDOWN:
-            self.drag_line_start = (px, py)
-        elif event == cv2.EVENT_LBUTTONUP:
+    def handleMouseEvent(self, event):
+        # get click position as distance to top-left corner of the image
+        px = event.pos().x()
+        py = self.img.height() - event.pos().y()
+        print(f"px = {px}, py = {py}")
+        if event.button() == QtCore.Qt.MouseButton.LeftButton:
+#            self.drag_line_start = (px, py)
+#        elif event == cv2.EVENT_LBUTTONUP:
             self.drag_line_end = (px, py)
+            self.drag_line_start = (px, py)
             target_pos = self.compute_clicked_position(self.drag_line_start[0], self.drag_line_start[1])
             if self.drag_line_start != self.drag_line_end:
                 # compute target angle for clicked position
@@ -155,106 +175,99 @@ class ArucoEstimator:
             if self.drag_line_start is not None:
                 self.drag_line_end = (px, py)
 
-    def run_tracking(self, draw_markers=True, draw_marker_coordinate_system=False, invert_grayscale=False):
-        """
-        Run the marker tracking in a loop
-        """
-        cv2.namedWindow('RoboRally', cv2.WINDOW_AUTOSIZE)
-        cv2.setMouseCallback('RoboRally', self.mouse_callback)
-
+    def process_frame(self):
+        draw_markers=True
+        draw_marker_coordinate_system=False
+        #cv2.setMouseCallback('RoboRally', self.mouse_callback)
         fps_display_rate = 1  # displays the frame rate every 1 second
-        fps_counter = 0
-        start_time = time.time()
-        try:
-            running = True
-            while running:
-                if self.pipeline:
-                    frames = self.pipeline.wait_for_frames()
-                    color_frame = frames.get_color_frame()
-                    if not color_frame:
-                        continue
-                    # Convert images to numpy arrays
-                    color_image = np.asanyarray(color_frame.get_data())
+        if self.pipeline:
+            frames = self.pipeline.wait_for_frames()
+            color_frame = frames.get_color_frame()
+            # if not color_frame:
+            #     continue
+            # Convert images to numpy arrays
+            color_image = np.asanyarray(color_frame.get_data())
+        else:
+            # Capture frame-by-frame
+            ret, color_image = self.cv_camera.read()
+        t_image = time.time()
+
+        gray = cv2.cvtColor(color_image, cv2.COLOR_BGR2GRAY)
+        if self.invert_grayscale:
+            cv2.bitwise_not(gray, gray)
+
+        # run aruco marker detection
+        detected_markers = self.detector.detect(gray)
+
+        # extract data for detected markers
+        detected_marker_data = {}
+        for marker in detected_markers:
+            if marker.id >= 0:
+                detected_marker_data[marker.id] = {'marker_center': marker.getCenter()}
+
+                if marker.id in self.corner_marker_ids.values():
+                    marker.calculateExtrinsics(0.075, self.camparam)
                 else:
-                    # Capture frame-by-frame
-                    ret, color_image = self.cv_camera.read()
-                t_image = time.time()
+                    marker.calculateExtrinsics(0.07, self.camparam)
+                detected_marker_data[marker.id]['Rvec'] = marker.Rvec
+                detected_marker_data[marker.id]['Tvec'] = marker.Tvec
 
-                gray = cv2.cvtColor(color_image, cv2.COLOR_BGR2GRAY)
-                if invert_grayscale:
-                    cv2.bitwise_not(gray, gray)
+                if draw_markers:
+                    marker.draw(color_image, np.array([255, 255, 255]), 2, True)
 
-                # run aruco marker detection
-                detected_markers = self.detector.detect(gray)
+                if draw_marker_coordinate_system:
+                    aruco.CvDrawingUtils.draw3dAxis(color_image, self.camparam, marker.Rvec, marker.Tvec, .1)
 
-                # extract data for detected markers
-                detected_marker_data = {}
-                for marker in detected_markers:
-                    if marker.id >= 0:
-                        detected_marker_data[marker.id] = {'marker_center': marker.getCenter()}
+        # store data
+        for marker_id, data in detected_marker_data.items():
+            self.update_estimate(marker_id, data['marker_center'], data['Rvec'], data['Tvec'], t_image)
 
-                        if marker.id in self.corner_marker_ids.values():
-                            marker.calculateExtrinsics(0.075, self.camparam)
-                        else:
-                            marker.calculateExtrinsics(0.07, self.camparam)
-                        detected_marker_data[marker.id]['Rvec'] = marker.Rvec
-                        detected_marker_data[marker.id]['Tvec'] = marker.Tvec
+        # draw grid
+        if self.draw_grid:
+            color_image = self.draw_grid_lines(color_image, detected_marker_data)
+        color_image = self.draw_robot_pos(color_image, detected_marker_data)
 
-                        if draw_markers:
-                            marker.draw(color_image, np.array([255, 255, 255]), 2, True)
+        # draw drag
+        if self.drag_line_start is not None and self.drag_line_end is not None:
+            color_image = cv2.line(color_image, self.drag_line_start, self.drag_line_end, color=(0, 0, 255), thickness=2)
 
-                        if draw_marker_coordinate_system:
-                            aruco.CvDrawingUtils.draw3dAxis(color_image, self.camparam, marker.Rvec, marker.Tvec, .1)
+        # compute frame rate
+        self.fps_counter += 1
+        delta_t = time.time() - self.fps_start_time
+        if delta_t > fps_display_rate:
+            self.fps_counter = 0
+            self.fps_start_time = time.time()
+        color_image = cv2.putText(color_image, f"fps = {(self.fps_counter / delta_t):.2f}", (10, 25), cv2.FONT_HERSHEY_PLAIN, 2,
+                                  (0, 255, 255),
+                                  thickness=2)
 
-                # store data
-                for marker_id, data in detected_marker_data.items():
-                    self.update_estimate(marker_id, data['marker_center'], data['Rvec'], data['Tvec'], t_image)
+        # Show images
+        color_image_rgb = cv2.cvtColor(color_image, cv2.COLOR_BGR2RGB)  # convert to RGB
+        self.img.setImage(np.transpose(np.flipud(color_image_rgb), axes=(1, 0, 2)))
 
-                # draw grid
-                if self.draw_grid:
-                    color_image = self.draw_grid_lines(color_image, detected_marker_data)
-                color_image = self.draw_robot_pos(color_image, detected_marker_data)
+        QtCore.QTimer.singleShot(1, self.process_frame)
 
-                # draw drag
-                if self.drag_line_start is not None and self.drag_line_end is not None:
-                    color_image = cv2.line(color_image, self.drag_line_start, self.drag_line_end, color=(0, 0, 255), thickness=2)
-
-                # compute frame rate
-                fps_counter += 1
-                delta_t = time.time() - start_time
-                if delta_t > fps_display_rate:
-                    fps_counter = 0
-                    start_time = time.time()
-                color_image = cv2.putText(color_image, f"fps = {(fps_counter / delta_t):.2f}", (10, 25), cv2.FONT_HERSHEY_PLAIN, 2,
-                                          (0, 255, 255),
-                                          thickness=2)
-
-                # Show images
-                cv2.imshow('RoboRally', color_image)
-                key = cv2.waitKey(1)
-
-                if key > 0:
-                    self.event_queue.put(('key', key))
-                    if key == ord('g'):
-                        self.draw_grid = not self.draw_grid
-                    if key == ord('q'):
-                        running = False
-                    if key == ord('x'):
-                        color_sensor = self.pipeline.get_active_profile().get_device().query_sensors()[1]
-                        if color_sensor.get_option(rs.option.enable_auto_exposure) == 1.0:
-                            color_sensor.set_option(rs.option.enable_auto_exposure, False)
-                            print("auto exposure OFF")
-                        else:
-                            color_sensor.set_option(rs.option.enable_auto_exposure, True)
-                            print("auto exposure ON")
-                    if key == ord('i'):
-                        invert_grayscale = not invert_grayscale
-        finally:
-            cv2.destroyAllWindows()
+    def handleKeyPressEvent(self, ev):
+        key = ev.key()
+        self.event_queue.put(('key', key))
+        if key == QtCore.Qt.Key_G:
+            self.draw_grid = not self.draw_grid
+        elif key == QtCore.Qt.Key_Q:
             if self.pipeline is not None:
                 # Stop streaming
                 self.pipeline.stop()
-
+            self.app.quit()
+        elif key == QtCore.Qt.Key_X:
+            if self.pipeline is not None:
+                color_sensor = self.pipeline.get_active_profile().get_device().query_sensors()[1]
+                if color_sensor.get_option(rs.option.enable_auto_exposure) == 1.0:
+                    color_sensor.set_option(rs.option.enable_auto_exposure, False)
+                    print("auto exposure OFF")
+                else:
+                    color_sensor.set_option(rs.option.enable_auto_exposure, True)
+                    print("auto exposure ON")
+        elif key == QtCore.Qt.Key_I:
+            self.invert_grayscale = not self.invert_grayscale
     def update_estimate(self, marker_id, pixel_coord_center, rvec, tvec, t_image):
         # update the marker estimate with new data
         if marker_id in self.corner_marker_ids.values():
@@ -445,5 +458,12 @@ class ArucoEstimator:
 
 
 if __name__ == "__main__":
-    estimator = ArucoEstimator(use_realsense=True, robot_marker_ids=[11, 12, 13, 14])
-    estimator.run_tracking(draw_markers=True, invert_grayscale=True)
+    estimator = ArucoEstimator(use_realsense=False, robot_marker_ids=[11, 12, 13, 14])
+    estimator.process_frame()
+
+    import sys
+
+    if (sys.flags.interactive != 1) or not hasattr(QtCore, 'PYQT_VERSION'):
+        QtGui.QApplication.instance().exec_()
+
+    #estimator.run_tracking(draw_markers=True, invert_grayscale=True)

remote_control/manual_controller.py

@@ -0,0 +1,62 @@
+import socket
+import pygame
+from argparse import ArgumentParser
+
+class ManualController:
+    def __init__(self, estimator):
+        self.estimator = estimator
+        self.estimator.external_keyboard_callback = self.handle_keypress
+
+        self.controlling = False
+
+    def handle_keypress(self, key):
+        pass
+
+parser = ArgumentParser()
+parser.add_argument('ip', metavar='ip', type=str, help='ip address of the controlled robot')
+args = parser.parse_args()
+
+ip = args.ip
+
+pygame.init()
+pygame.display.set_mode((640, 480))
+
+rc_socket = socket.socket()
+try:
+    rc_socket.connect((ip, 1234)) # connect to robot
+except socket.error:
+    print("could not connect to socket")
+
+running = True
+while running:
+    u1 = 0
+    u2 = 0
+    vmax = 1.0
+    events = pygame.event.get()
+    for event in events:
+        if event.type == pygame.KEYDOWN:
+            if event.key == pygame.K_LEFT:
+                u1 = -vmax 
+                u2 = vmax
+                print(f"turn left: ({u1},{u2})")
+            elif event.key == pygame.K_RIGHT:
+                u1 = vmax
+                u2 = -vmax
+                print(f"turn right: ({u1},{u2})")
+            elif event.key == pygame.K_UP:
+                u1 = vmax
+                u2 = vmax
+                print(f"forward: ({u1},{u2})")
+            elif event.key == pygame.K_DOWN:
+                u1 = -vmax 
+                u2 = -vmax 
+                print(f"backward: ({u1},{u2})")
+            elif event.key == pygame.K_ESCAPE:
+                print("quit")
+                running = False
+                u1 = 0.0
+                u2 = 0.0
+            rc_socket.send(f'({u1},{u2})\n'.encode())
+        elif event.type == pygame.KEYUP:
+            print("key released, resetting: ({},{})".format(u1, u2))
+            rc_socket.send(f'({u1},{u2})\n'.encode())

remote_control/mensaabend.py

@@ -0,0 +1,117 @@
+from flask import Flask, render_template, request
+
+import socket
+import threading
+import time
+import numpy as np
+
+from robot import Robot
+
+from mpc_controller import MPCController
+from aruco_estimator import ArucoEstimator
+
+from shapely.geometry import LineString
+
+width = 600
+height = 400
+
+robot_ids = [11, 12, 13, 14]
+robot_ids_control_history = [11, 12, 13, 14]
+
+app = Flask(__name__)
+
+def calc_target_pos(px, py):
+    if rc.estimator.all_corners_detected():
+        # compute column line
+        a = np.array([rc.estimator.corner_estimates['a']['x'], rc.estimator.corner_estimates['a']['y']])
+        b = np.array([rc.estimator.corner_estimates['b']['x'], rc.estimator.corner_estimates['b']['y']])
+        c = np.array([rc.estimator.corner_estimates['c']['x'], rc.estimator.corner_estimates['c']['y']])
+        d = np.array([rc.estimator.corner_estimates['d']['x'], rc.estimator.corner_estimates['d']['y']])
+        x_frac = (px + 0.5) / width
+        y_frac = (py + 0.5) / height
+
+        vab = b - a
+        vdc = c - d
+        column_line_top = a + x_frac * vab
+        column_line_bottom = d + x_frac * vdc
+
+        vad = d - a
+        vbc = c - b
+        row_line_top = a + y_frac * vad
+        row_line_bottom = b + y_frac * vbc
+
+        column_line = LineString([column_line_top, column_line_bottom])
+        row_line = LineString([row_line_top, row_line_bottom])
+
+        int_pt = column_line.intersection(row_line)
+        point_of_intersection = np.array([int_pt.x, int_pt.y, 0.0])
+
+        return point_of_intersection
+
+
+@app.route('/', methods=('GET', 'POST'))
+def presence():
+    global robot_ids_control_history
+    if request.method == 'GET':
+        return render_template('telepresence.html', oldest_control=robot_ids.index(robot_ids_control_history[0]))
+    elif request.method == 'POST':
+        x = int(float(request.form.get('x')))
+        y = int(float(request.form.get('y')))
+        print(x, y)
+        margin = 0.1
+        x = min(max(width * margin, x), width * (1 - margin))
+        y = min(max(height * margin, y), height * (1 - margin))
+
+        id = int(request.form.get('robot'))
+        robot_ids_control_history.append(robot_ids_control_history.pop(robot_ids_control_history.index(id)))
+
+        target_pos = calc_target_pos(x, y)
+        rc.estimator.event_queue.put(('robot', id, target_pos))
+
+        return 'OK'
+
+
+class RemoteController:
+    def __init__(self):
+        self.robots = []
+        #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')

remote_control/templates/telepresence.html

@@ -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>