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How to use multi_scale_search method in Airtest

Best Python code snippet using Airtest

play.py

Source:play.py

...8import shutil9import time10import cv211import numpy as np12def multi_scale_search(pivot, screen, range=0.3, num=10):13    H, W = screen.shape[:2]14    h, w = pivot.shape[:2]15    found = None16    for scale in np.linspace(1 - range, 1 + range, num)[::-1]:17        resized = cv2.resize(screen, (int(W * scale), int(H * scale)))18        r = W / float(resized.shape[1])19        if resized.shape[0] < h or resized.shape[1] < w:20            break21        res = cv2.matchTemplate(resized, pivot, cv2.TM_CCOEFF_NORMED)22        loc = np.where(res >= res.max())23        pos_h, pos_w = list(zip(*loc))[0]24        if found is None or res.max() > found[-1]:25            found = (pos_h, pos_w, r, res.max())26    if found is None: return (0, 0, 0, 0, 0)27    pos_h, pos_w, r, score = found28    start_h, start_w = int(pos_h * r), int(pos_w * r)29    end_h, end_w = int((pos_h + h) * r), int((pos_w + w) * r)30    return [start_h, start_w, end_h, end_w, score]31class WechatAutoJump(object):32    def __init__(self, sensitivity, debug, resource_dir):33        self.sensitivity = sensitivity34        self.debug = debug35        self.resource_dir = resource_dir36        self.bb_size = [300, 300]37        self.step = 138        self.load_resource()39        if self.debug:40            if not os.path.exists(self.debug):41                os.mkdir(self.debug)42    def load_resource(self):43        self.player = cv2.imread(os.path.join(self.resource_dir, 'player.png'), 0)44        circle_file = glob.glob(os.path.join(self.resource_dir, 'circle/*.png'))45        table_file = glob.glob(os.path.join(self.resource_dir, 'table/*.png'))46        self.jump_file = [cv2.imread(name, 0) for name in circle_file + table_file]47    def get_current_state(self):48        pic_filename = 'state{:03d}.png'.format(self.step)49        state = cv2.imread(pic_filename)50        self.resolution = state.shape[:2]51        scale = state.shape[1] / 720.52        state = cv2.resize(state, (720, int(state.shape[0] / scale)), interpolation=cv2.INTER_NEAREST)53        if state.shape[0] > 1280:54            s = (state.shape[0] - 1280) // 255            state = state[s:(s + 1280), :, :]56        elif state.shape[0] < 1280:57            s1 = (1280 - state.shape[0]) // 258            s2 = (1280 - state.shape[0]) - s159            pad1 = 255 * np.ones((s1, 720, 3), dtype=np.uint8)60            pad2 = 255 * np.ones((s2, 720, 3), dtype=np.uint8)61            state = np.concatenate((pad1, state, pad2), 0)62        return state63    def get_player_position(self, state):64        state = cv2.cvtColor(state, cv2.COLOR_BGR2GRAY)65        pos = multi_scale_search(self.player, state, 0.3, 10)66        h, w = int((pos[0] + 13 * pos[2]) / 14.), (pos[1] + pos[3]) // 267        return np.array([h, w])68    def get_target_position(self, state, player_pos):69        state = cv2.cvtColor(state, cv2.COLOR_BGR2GRAY)70        sym_center = [1280, 720] - player_pos71        sym_tl = np.maximum([0, 0], sym_center + np.array([-self.bb_size[0] // 2, -self.bb_size[1] // 2]))72        sym_br = np.array(73            [min(sym_center[0] + self.bb_size[0] // 2, player_pos[0]), min(sym_center[0] + self.bb_size[1] // 2, 720)])74        state_cut = state[sym_tl[0]:sym_br[0], sym_tl[1]:sym_br[1]]75        target_pos = None76        for target in self.jump_file:77            pos = multi_scale_search(target, state_cut, 0.4, 15)78            if target_pos is None or pos[-1] > target_pos[-1]:79                target_pos = pos80        return np.array([(target_pos[0] + target_pos[2]) // 2, (target_pos[1] + target_pos[3]) // 2]) + sym_tl81    def get_target_position_fast(self, state, player_pos):82        state_cut = state[:player_pos[0], :, :]83        m1 = (state_cut[:, :, 0] == 245)84        m2 = (state_cut[:, :, 1] == 245)85        m3 = (state_cut[:, :, 2] == 245)86        m = np.uint8(np.float32(m1 * m2 * m3) * 255)87        b1, b2 = cv2.connectedComponents(m)88        for i in range(1, np.max(b2) + 1):89            x, y = np.where(b2 == i)90            # print('fast', len(x))91            if len(x) > 280 and len(x) < 310:...

main.py

Source:main.py

1import cv2;2import numpy as np3import os, glob, shutil4import random5def multi_scale_search(pivot, screen, range=0.3, num=10):6    H, W = screen.shape[:2]7    h, w = pivot.shape[:2]8    found = None9    for scale in np.linspace(1-range, 1+range, num)[::-1]:10        resized = cv2.resize(screen, (int(W * scale), int(H * scale)))11        r = W / float(resized.shape[1])12        if resized.shape[0] < h or resized.shape[1] < w:13            break14        res = cv2.matchTemplate(resized, pivot, cv2.TM_CCOEFF_NORMED)15        loc = np.where(res >= res.max())16        pos_h, pos_w = list(zip(*loc))[0]17        if found is None or res.max() > found[-1]:18            found = (pos_h, pos_w, r, res.max())19    if found is None: return (0,0,0,0,0)20    pos_h, pos_w, r, score = found21    start_h, start_w = int(pos_h * r), int(pos_w * r)22    end_h, end_w = int((pos_h + h) * r), int((pos_w + w) * r)23    return [start_h, start_w, end_h, end_w, score]24class wechat_jump(object):25	def __init__(self):26		self.resource_dir = "./resources"27		self.sensitivity = 2.04528		self.bb_size = [300, 300]29		self.load_resources()30		31	def load_resources(self):32		self.player = cv2.imread(os.path.join(self.resource_dir + '/position/player.png'), 0)33		circle_file = glob.glob(os.path.join(self.resource_dir + '/position/circle/*.png'))34		table_file  = glob.glob(os.path.join(self.resource_dir + '/position/table/*.png'))35		self.jump_file = [cv2.imread(name, 0) for name in circle_file + table_file]36	def get_player_position(self, state):37		state = cv2.cvtColor(state, cv2.COLOR_BGR2GRAY)38		pos = multi_scale_search(self.player, state, 0.3, 10)39		h, w = int((pos[0] + 13 * pos[2])/14.), (pos[1] + pos[3])//240		return np.array([h, w])41	def get_target_position_fast(self, state, player_pos):42		state_cut = state[:player_pos[0],:,:]43		m1 = (state_cut[:, :, 0] == 245)44		m2 = (state_cut[:, :, 1] == 245)45		m3 = (state_cut[:, :, 2] == 245)46		m = np.uint8(np.float32(m1 * m2 * m3) * 255)47		b1, b2 = cv2.connectedComponents(m)48		for i in range(1, np.max(b2) + 1):49			x, y = np.where(b2 == i)50			# print('fast', len(x))51			if len(x) > 280 and len(x) < 310:52				r_x = []53				r_y = x, y54		h, w = int(r_x.mean()), int(r_y.mean())55		return np.array([h, w])56	def get_target_position(self, state, player_pos):57		state = cv2.cvtColor(state, cv2.COLOR_BGR2GRAY)58		sym_center = [1280, 720] - player_pos59		sym_tl = np.maximum([0,0], sym_center + np.array([-self.bb_size[0]//2, -self.bb_size[1]//2]))60		sym_br = np.array([min(sym_center[0] + self.bb_size[0]//2, player_pos[0]), min(sym_center[0] + self.bb_size[1]//2, 720)])61		state_cut = state[sym_tl[0]:sym_br[0], sym_tl[1]:sym_br[1]]62		target_pos = None63		for target in self.jump_file:64			pos = multi_scale_search(target, state_cut, 0.4, 15)65			if target_pos is None or pos[-1] > target_pos[-1]:66				target_pos = pos67		return np.array([(target_pos[0]+target_pos[2])//2, (target_pos[1]+target_pos[3])//2]) + sym_tl68	def get_state(self):69		# state image70		# os.system('adb shell screencap -p /sdcard/state.png')71		# os.system('adb pull /sdcard/state.png ' + self.resource_dir + '/screen/state.png')72		state = cv2.imread(self.resource_dir + '/screen/state.png')73		self.resolution = state.shape[:2]74		scale = state.shape[1] / 720.075		state = cv2.resize(state, (720, int(state.shape[0] / scale)), interpolation=cv2.INTER_NEAREST)76		if state.shape[0] > 1280:77			s = state.shape[0] - 128078			state = state[s:,:,:]...

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