| #!/usr/bin/python3 |
| |
| import cv2 as cv |
| from enum import Enum |
| import glog |
| import json |
| import matplotlib.pyplot as plt |
| import numpy as np |
| import os |
| |
| class Rect: |
| |
| # x1 and y1 are top left corner, x2 and y2 are bottom right |
| def __init__(self, x1, y1, x2, y2): |
| self.x1 = x1 |
| self.y1 = y1 |
| self.x2 = x2 |
| self.y2 = y2 |
| |
| def __str__(self): |
| return "({}, {}), ({}, {})".format(self.x1, self.y1, self.x2, self.y2) |
| |
| def to_list(self): |
| return [self.x1, self.y1, self.x2, self.y2] |
| |
| @classmethod |
| def from_list(cls, list): |
| rect = None |
| if len(list) == 4: |
| rect = cls(list[0], list[1], list[2], list[3]) |
| else: |
| glog.error("Expected list len to be 4 but it was %u", len(list)) |
| rect = cls(None, None, None, None) |
| return rect |
| |
| |
| class Alliance(Enum): |
| kRed = "red" |
| kBlue = "blue" |
| kUnknown = None |
| |
| @staticmethod |
| def from_value(value): |
| return (Alliance.kRed if value == Alliance.kRed.value else Alliance.kBlue) |
| |
| @staticmethod |
| def from_name(name): |
| return (Alliance.kRed if name == Alliance.kRed.name else Alliance.kBlue) |
| |
| class Letter(Enum): |
| kA = 'A' |
| kB = 'B' |
| |
| @staticmethod |
| def from_value(value): |
| return (Letter.kA if value == Letter.kA.value else Letter.kB) |
| |
| @staticmethod |
| def from_name(name): |
| return (Letter.kA if name == Letter.kA.name else Letter.kB) |
| |
| class Path: |
| |
| def __init__(self, letter, alliance, rects): |
| self.letter = letter |
| self.alliance = alliance |
| self.rects = rects |
| |
| def __str__(self): |
| return "%s %s: " % (self.alliance.value, self.letter.value) |
| |
| def to_dict(self): |
| return {"alliance": self.alliance.name, "letter": self.letter.name} |
| |
| RECTS_JSON_PATH = "rects.json" |
| |
| AOS_SEND_PATH = "bazel-bin/aos/aos_send" |
| |
| def setup_if_pi(): |
| if os.path.isdir("/home/pi/robot_code"): |
| AOS_SEND_PATH = "/home/pi/robot_code/aos_send.stripped" |
| os.system("./starter_cmd stop camera_reader") |
| |
| setup_if_pi() |
| |
| # The minimum percentage of yellow for a region of a image to |
| # be considered to have a ball |
| BALL_PCT_THRESHOLD = 0.1 |
| |
| _paths = [] |
| |
| def load_json(): |
| rects_dict = None |
| with open(RECTS_JSON_PATH, 'r') as rects_json: |
| rects_dict = json.load(rects_json) |
| return rects_dict |
| |
| def _run_detection_loop(): |
| global img_fig, rects_dict |
| |
| rects_dict = load_json() |
| for letter in rects_dict: |
| for alliance in rects_dict[letter]: |
| rects = [] |
| for rect_list in rects_dict[letter][alliance]: |
| rects.append(Rect.from_list(rect_list)) |
| _paths.append(Path(Letter.from_name(letter), Alliance.from_name(alliance), rects)) |
| |
| plt.ion() |
| img_fig = plt.figure() |
| |
| running = True |
| while running: |
| _detect_path() |
| |
| def _detect_path(): |
| img = capture_img() |
| img_fig.figimage(img) |
| plt.show() |
| |
| plt.pause(0.001) |
| |
| mask = _create_mask(img) |
| |
| current_path = None |
| num_current_paths = 0 |
| for path in _paths: |
| pcts = _pct_yellow(mask, path.rects) |
| if len(pcts) == len(path.rects): |
| glog.info(path) |
| for i in range(len(pcts)): |
| glog.info("Percent yellow of %s: %f", path.rects[i], pcts[i]) |
| glog.info("") |
| |
| # If all the balls in a path were detected then that path is present |
| rects_with_balls = np.where(pcts >= BALL_PCT_THRESHOLD)[0].size |
| if rects_with_balls == len(path.rects): |
| current_path = path |
| num_current_paths += 1 |
| else: |
| glog.error("Error: len of pcts (%u) != len of rects: (%u)", len(pcts), len(rects)) |
| |
| if num_current_paths != 1: |
| if num_current_paths == 0: |
| current_path = Path(Letter.kA, None, None) |
| current_path.alliance = Alliance.kUnknown |
| glog.warn("Expected 1 path but detected %u", num_current_paths) |
| return |
| |
| |
| path_dict = current_path.to_dict() |
| glog.info("Path is %s", path_dict) |
| os.system(AOS_SEND_PATH + |
| " /pi2/camera y2020.vision.GalacticSearchPath '" + json.dumps(path_dict) + "'") |
| |
| KERNEL = np.ones((5, 5), np.uint8) |
| |
| def _create_mask(img): |
| hsv = cv.cvtColor(img, cv.COLOR_BGR2HSV) |
| lower_yellow = np.array([23, 100, 75], dtype = np.uint8) |
| higher_yellow = np.array([40, 255, 255], dtype = np.uint8) |
| mask = cv.inRange(hsv, lower_yellow, higher_yellow) |
| mask = cv.erode(mask, KERNEL, iterations = 1) |
| mask = cv.dilate(mask, KERNEL, iterations = 3) |
| |
| return mask |
| |
| # This function finds the percentage of yellow pixels in the rectangles |
| # given that are regions of the given image. This allows us to determine |
| # whether there is a ball in those rectangles |
| def _pct_yellow(mask, rects): |
| pcts = np.zeros(len(rects)) |
| for i in range(len(rects)): |
| rect = rects[i] |
| slice = mask[rect.y1 : rect.y2, rect.x1 : rect.x2] |
| yellow_px = np.count_nonzero(slice) |
| pcts[i] = yellow_px / (slice.shape[0] * slice.shape[1]) |
| |
| return pcts |
| |
| _video_stream = cv.VideoCapture(0) |
| |
| def capture_img(): |
| global _video_stream |
| return _video_stream.read()[1] |
| |
| def release_stream(): |
| global _video_stream |
| _video_stream.release() |
| |
| def main(): |
| _run_detection_loop() |
| release_stream() |
| |
| if __name__ == "__main__": |
| main() |