整个项目在https://github.com/ximikang/ffmpegThumbnail发布

生成缩略图的步骤

1. 使用ffmpeg解码视频
2. 帧格式转换
3. 根据缩略图的数量从视频流中取帧
4. 使用opencv建立画布并生成缩略图

ffmpeg解码视频

根据缩略图的数量从视频流中取帧

1. 获取图片之间的时间间隔

   // Read media file and read the header information from container format
   AVFormatContext* pFormatContext = avformat_alloc_context();
   if (!pFormatContext) {
   	logging("ERROR could not allocate memory for format context");
   	return -1;
   }
   
   if (avformat_open_input(&pFormatContext, inputFilePath.string().c_str(), NULL, NULL) != 0) {
   	logging("ERROR could not open media file");
   }
   
   logging("format %s, duration %lld us, bit_rate %lld", pFormatContext->iformat->name, pFormatContext->duration, pFormatContext->bit_rate);
   cout << "视频时常：" << pFormatContext->duration / 1000.0 / 1000.0 << "s" << endl;
   int64_t video_duration = pFormatContext->duration;
   int sum_count = rowNums * colNums;
   //跳转的间隔 ms
   int64_t time_step = video_duration / sum_count / 1000;

2. 设置跳转时间获取不同的视频Packet

   for (int i = 0; i < sum_count ; ++i) {
   	cv::Mat tempImage;
   	// 每次读取相同时间间隔的图像并存入vImage中
   	while (av_read_frame(pFormatContext, pPacket) >= 0) {
   		if (pPacket->stream_index == video_stream_index) {
   			response = decode_packet_2mat(pPacket, pCodecContext, pFrame, tempImage);// 返回
   		}
   		if (response == 0)// 成功读取一帧
   			break;
   		if (response < 0)
   			continue;
   	}
   	vImage.push_back(tempImage);
   	// 跳转视频
   	av_seek_frame(pFormatContext, -1, ((double)time_step / (double)1000)* AV_TIME_BASE*(double)(i+1) + (double)pFormatContext->start_time, AVSEEK_FLAG_BACKWARD);
   }

3. 获取Frame
   在固定的时间点可能无法获取从当前时间点的Packet获取对应的Frame，所以需要对获取的Packet进行判断，如果没有获取到对应的Frame应该继续获取下一Packet直到获取到对应的Frame为止。

   static int decode_packet_2mat(AVPacket* pPacket, AVCodecContext* pCodecContext, AVFrame* pFrame, cv::Mat& image) {
   	int response = avcodec_send_packet(pCodecContext, pPacket);
   
   	if (response < 0) {
   		logging("Error while sending a packet to the decoder");
   		return response;
   	}
   
   	while (response >= 0) {
   		// return decoded out data from a decoder
   		response = avcodec_receive_frame(pCodecContext, pFrame);
   		if (response == AVERROR(EAGAIN) || response == AVERROR_EOF) {
   			logging("averror averror_eof");
   			break;
   		}
   		else if (response < 0) {
   			logging("Error while receiving frame");
   			return response;
   		}
   
   		if (response >= 0) {
   			// 获取到Frame
   			image = frame2Mat(pFrame, pCodecContext->pix_fmt);
   		} 
   		return 0;
   	}
   }

   帧格式转换

   由于从视频流获取的帧是YUV格式的Frame格式，后面使用opencv进行操作所以进行格式转换。

先使用ffmpeg中的SwsContext将从视频中抽取到的帧从YUV转换到BGR格式，再从BGRFrame中的内存中获取原始数据，并转换到opencv的Mat类型。

cv::Mat frame2Mat(AVFrame* pFrame, AVPixelFormat pPixFormat)
{
	// image init
	AVFrame* pRGBFrame = av_frame_alloc();
	uint8_t* out_buffer = new uint8_t[avpicture_get_size(AV_PIX_FMT_BGR24, pFrame->width, pFrame->height)];
	avpicture_fill((AVPicture*)pRGBFrame, out_buffer, AV_PIX_FMT_BGR24, pFrame->width, pFrame->height);
	SwsContext* rgbSwsContext = sws_getContext(pFrame->width, pFrame->height, pPixFormat, pFrame->width, pFrame->height, AV_PIX_FMT_BGR24,SWS_BICUBIC, NULL, NULL, NULL);
	if (!rgbSwsContext) {
		logging("Error could not create frame to rgbframe sws context");
		exit(-1);
	}
	if (sws_scale(rgbSwsContext, pFrame->data, pFrame->linesize, 0, pFrame->height, pRGBFrame->data, pRGBFrame->linesize) < 0) {
		logging("Error could not sws to rgb frame");
		exit(-1);
	}

	cv::Mat mRGB(cv::Size(pFrame->width, pFrame->height), CV_8UC3);
	mRGB.data = (uchar*)pRGBFrame->data[0];//注意不能写为：(uchar*)pFrameBGR->data

	av_free(pRGBFrame);
	sws_freeContext(rgbSwsContext);
	return mRGB;
}

使用opencv建立画布并生成缩略图

通过画布需要的大小参数，画出白色画布，再对画布进行填充。

cv::Mat makeThumbnail(vector<cv::Mat> vImage, const unsigned int rowNums, const unsigned int colNums)
{
	// 判断图片时候满足条件
	if (vImage.size() != rowNums * colNums) {
		logging("Error image size not equal input size");
		logging("vImage length: %d, rowNums: %d, col number: %d", vImage.size(), rowNums, colNums);
		exit(-1);
	}
	int interval = 100;
	int height = vImage[0].size().height * rowNums + interval * (rowNums + 1);
	int width = vImage[0].size().width * colNums + interval * (colNums + 1);
	logging("thumbnail size: %d * %d", height, width);
	cv::Mat thumbnail(cv::Size(width, height), CV_8UC3);
	thumbnail.setTo(255);

	// 进行填充
	for (int i = 0; i < rowNums; ++i) {
		for (int j = 0; j < colNums; ++j) {
			int no = i * rowNums + j;
			int widthOffset = (vImage[0].size().width + interval) * j + interval;
			int heightOffset = (vImage[0].size().height + interval) * i + interval;
			vImage[no].copyTo(thumbnail(cv::Rect(widthOffset, heightOffset, vImage[0].size().width, vImage[0].size().height)));
		}
	}
	return thumbnail;
}

最后的效果