在虚拟机上，大约700毫秒一帧，性能无法忍受。
import cv2 import numpy as np import time def dehaze(image, w=1, t0=0.4, p=0.8): # 估计全局大气光照 dark_channel = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY) dark_channel = cv2.min(dark_channel, cv2.blur(dark_channel, (15, 15))) hist = cv2.calcHist([dark_channel], [0], None, [256], [0, 256]) hist_cum = hist.cumsum() percentile = (1 - w) * hist_cum[-1] atmospheric_light = 255 - np.argmax(hist_cum > percentile) # 估计透射率 normalized_image = np.uint8(image / atmospheric_light) # 将数据类型转换为8位无符号整数 dark_channel = cv2.min(cv2.cvtColor(normalized_image, cv2.COLOR_BGR2GRAY), cv2.blur(dark_channel, (15, 15))) transmission = 1 - t0 * dark_channel # 双边滤波 guide = cv2.GaussianBlur(image, (0, 0), p) dehazed_image = np.zeros_like(image) for i in range(3): dehazed_image[:, :, i] = (image[:, :, i] - atmospheric_light) / cv2.max(transmission, 0.1) + atmospheric_light dehazed_image = guide * transmission[:, :, np.newaxis] + dehazed_image * (1 - transmission[:, :, np.newaxis]) return dehazed_image.astype(np.uint8) def real_time_dehazing(input_file, output_file): cap = cv2.VideoCapture(input_file) fps = int(cap.get(cv2.CAP_PROP_FPS)) width = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH)) height = int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT)) # 初始化视频写入器 merge = True write_w= width if (merge): write_w += width fourcc = cv2.VideoWriter_fourcc(*'mp4v') out = cv2.VideoWriter(output_file, fourcc, fps, (write_w, height)) counter= 0 cost = 0 while True: ret, frame = cap.read() if not ret: break counter += 1 # 超快速去雾 start_time = time.time() result = dehaze(frame) time_ms = (time.time() - start_time)*1000 cost += time_ms print(counter, int(time_ms)) # 显示 cv2.putText(result, f"{time_ms:.1f}ms", (30, 100), cv2.FONT_HERSHEY_SIMPLEX, 0.7, (0, 255, 0), 2) if (merge): result = cv2.hconcat([frame, result]); out.write(result) print(cost, '/', counter, '=', (cost/counter)) out.release() cap.release() input_file = '../test-files/fog5-1920x1080.mp4' output_file = 'defog.mp4' real_time_dehazing(input_file, output_file)
