// 显示相似图片左右两侧
private void dataGridView1_SelectionChanged(object sender, EventArgs e)
{
if (this.dataGridView1.SelectedRows != null && this.dataGridView1.SelectedRows.Count > 0)
{
int current_row = this.dataGridView1.SelectedRows[0].Index; //int current_row = this.dataGridView1.CurrentRow.Index;
DataGridViewCell cell = this.dataGridView1.Rows[current_row].Cells[0];
if (cell.Value.ToString() != "")
{
this.row_id = cell.Value.ToString(); // 当前行的编号
this.row = this.dataGridView1.CurrentCell.RowIndex; // 当前行行数
List <ImageGroup> select_ig = this.ig_group.Where(x => x.id == this.row_id).ToList(); //查询是哪一个ImageGroup
ImageGroup ig = select_ig[0];
this.left_url = ig.left_url;
this.right_url = ig.right_url;
this.pictureBox1.Image = ImageUtils.GetImage(this.left_url);
this.left_title_label.Text = this.left_url.Substring(this.left_url.LastIndexOf("\\") + 1);
this.left_infos_label.Text = ig.left_modify_time + " " + ig.left_size + " " + ig.left_resolution;
this.pictureBox2.Image = ImageUtils.GetImage(this.right_url);
this.right_title_label.Text = this.right_url.Substring(this.right_url.LastIndexOf("\\") + 1);
this.right_infos_label.Text = ig.right_modify_time + " " + ig.right_size + " " + ig.right_resolution;
}
}
}
// 建立表格中的数据
private void GetDataTable(String action)
{
// 重新加载数据表
this.dt.Clear();
// 选择符合条件的ImageGroup数据
if (action == "new")
{
if (this.view_ig_group != null)
{
this.view_ig_group.Clear();
}
this.view_ig_group = this.ig_group.Where(x => x.simliar_val >= this.similar_val).ToList();
}
else if (action == "filter")
{
// 选择符合条件的ImageGroup数据
this.view_ig_group = this.view_ig_group.Where(x => x.simliar_val >= this.similar_val).ToList();
}
// DataGridView填充所有的数据
for (int i = 0; i < this.view_ig_group.Count; i++)
{
DataRow new_dr = this.dt.NewRow();
this.dt.Rows.Add(new_dr);
ImageGroup ig = this.view_ig_group[i];
this.dt.Rows[i][0] = ig.id;
this.dt.Rows[i][1] = ig.left_url;
this.dt.Rows[i][2] = ig.left_resolution;
this.dt.Rows[i][3] = ig.right_url;
this.dt.Rows[i][4] = ig.right_resolution;
this.dt.Rows[i][5] = ig.simliar_val * 100;
}
this.dataGridView1.DataSource = this.dt;
// 设置dataGrid表格的宽度
this.dataGridView1.Columns[0].Width = 60;
this.dataGridView1.Columns[1].Width = 250;
this.dataGridView1.Columns[2].Width = 85;
this.dataGridView1.Columns[3].Width = 250;
this.dataGridView1.Columns[4].Width = 85;
this.dataGridView1.Columns[5].Width = 80;
}
// 多线程计算相似度
private void ComputeSimilar(object obj)
{
while (true)
{
if (this.finish_readimg)
{
break;
}
Thread.Sleep(1);
}
int N = this.compare_idx.Length / 2;
int group_idx = (int)obj;
int start_index = group_idx * N / this.thread_num; // 比较开始的坐标
int end_idex = -1;
if (group_idx + 1 == this.thread_num)
{
end_idex = N - 1;
}
else
{
end_idex = start_index + N / this.thread_num - 1;
}
for (int i = start_index; i <= end_idex; i++)
{
int left_idx = this.compare_idx[i, 0];
int right_idx = this.compare_idx[i, 1];
ImageHashObj left_iho = this.iho_group[left_idx];
ImageHashObj right_iho = this.iho_group[right_idx];
int dhash_degree = ImageUtils.CalcSimilarDegree(left_iho.dHash, right_iho.dHash); // dhash的Hamming距离
double dhash_similar = ((double)(W * H - dhash_degree)) / (W * H); // 计算dhash相似度
double images_similar = dhash_similar;
//double size1 = double.Parse(left_iho.h) / double.Parse(left_iho.w);
//double size2 = double.Parse(right_iho.h) / double.Parse(right_iho.w);
//double size_similar = 1 - (Math.Max(size1, size2) - Math.Min(size1, size2)) / Math.Max(size1, size2);
//if (size_similar < 0.90){
// if (left_iho.hisogram == null)
// left_iho.hisogram = ImageUtils.GetHisogram(left_iho.url);
// if (right_iho.hisogram == null)
// right_iho.hisogram = ImageUtils.GetHisogram(right_iho.url);
// double hisogram_similar = ImageUtils.CalHistogramSimilar(left_iho.hisogram, right_iho.hisogram); // 计算直方图相似度
// images_similar = dhash_similar * weight[0] + hisogram_similar * weight[1];
//}
ImageGroup ig = new ImageGroup();
ig.id = i + "";
ig.left_url = left_iho.url;
ig.left_modify_time = left_iho.modify_time;
ig.left_size = left_iho.size;
ig.left_resolution = left_iho.w + "×" + left_iho.h;
ig.right_url = right_iho.url;
ig.right_modify_time = right_iho.modify_time;
ig.right_size = right_iho.size;
ig.right_resolution = right_iho.w + "×" + right_iho.h;
ig.simliar_val = images_similar;
lock (this.ig_group) {
this.ig_group.Add(ig);
}
lock ((object)this.progreassbar_num){
this.progreassbar_num++;
}
// 如果UTC时间是整100毫秒
if (i % this.compare_load_num == 0)
{
TimeSpan ts = DateTime.UtcNow - new DateTime(1970, 1, 1, 0, 0, 0, 0);
long time_int = (long)(ts.TotalMilliseconds * 1000);
SetTextMesssage("compare_bar");
}
}
lock ((object)this.process_group) {
this.process_group++;
}
}
// 点击分析按按钮
private void button6_Click(object sender, EventArgs e)
{
// 刷新左侧和右侧
this.left_url = "";
this.left_title_label.Text = "";
this.left_infos_label.Text = "";
this.pictureBox1.Image = null;
this.right_url = "";
this.right_title_label.Text = "";
this.right_infos_label.Text = "";
this.pictureBox2.Image = null;
this.textBox3.Text = "";
this.progressBar2.Value = 0;
// 读取相似度设置
this.similar_val = double.Parse(this.numericUpDown1.Value.ToString()) / 100;
if (this.fold_group.Count == 0)
{
MessageBox.Show("请选择要添加的文件夹");
}
else
{
this.all_images_group = new List <String>();
this.iho_group = new List <ImageHashObj>();
this.process_group = 0;
ImageUtils.W = W;
ImageUtils.H = H;
this.dt.Clear(); // 清空数据表
foreach (String dir_path in fold_group) // 遍历所有的图片
{
FileUtils.getAllImages(this.all_images_group, dir_path);
}
this.textBox1.Text = "0/" + this.all_images_group.Count; //显示有多少张图片
this.progreassbar_num = 0; // 重置进度条
this.textBox2.Text = "正在读取图片和计算图片的特征值";
//// 如果图片数量过多则多线程处理
int sub_num = all_images_group.Count / thread_num;
if (sub_num == 0 || this.thread_num == 1) // 如果图片小于线程数则单线程处理
{
// 读取所有图片并计算dhash特征值
for (int i = 0; i < all_images_group.Count; i++)
{
String image_url = all_images_group[i];
String[] image_info_str = ImageUtils.GetHash(image_url);
if (image_info_str != null)
{
ImageHashObj iho = new ImageHashObj();
iho.name = image_info_str[0];
iho.url = image_info_str[1];
iho.h = image_info_str[2];
iho.w = image_info_str[3];
iho.size = image_info_str[4];
iho.modify_time = image_info_str[5];
iho.dHash = image_info_str[6];
this.iho_group.Add(iho);
}
this.progreassbar_num++;
if (i % 10 == 0)
{
SetTextMesssage("read_bar");
}
}
SetTextMesssage("read_bar");
getSimilarImages("所有图片的hash已经计算完成");
iho_group.Sort((x, y) => x.url.CompareTo(y.url)); // 计算完所有的hash之后对iho_group按照文件名排序
int count = 0;
this.ig_group = new List <ImageGroup>();
// 比较所有的图片
for (int left_idx = 0; left_idx < this.iho_group.Count - 1; left_idx++)
{
for (int right_idx = left_idx + 1; right_idx < this.iho_group.Count - 1; right_idx++)
{
ImageHashObj left_iho = this.iho_group[left_idx];
ImageHashObj right_iho = this.iho_group[right_idx];
int dhash_degree = ImageUtils.CalcSimilarDegree(left_iho.dHash, right_iho.dHash); // dhash的Hamming距离
double dhash_similar = ((double)(W * H - dhash_degree)) / (W * H); // 计算dhash相似度
double images_similar = dhash_similar;
images_similar = Math.Round(images_similar, 3); // 保留三位小数
ImageGroup ig = new ImageGroup();
// 根据UTC时间戳生成唯一的主键
ig.id = ++count + "";
ig.left_url = left_iho.url;
ig.left_modify_time = left_iho.modify_time;
ig.left_size = left_iho.size;
ig.left_resolution = left_iho.w + "×" + left_iho.h;
ig.right_url = right_iho.url;
ig.right_modify_time = right_iho.modify_time;
ig.right_size = right_iho.size;
ig.right_resolution = right_iho.w + "×" + right_iho.h;
ig.simliar_val = images_similar;
this.ig_group.Add(ig);
this.progreassbar_num++;
if (right_idx % 50 == 0)
{
SetTextMesssage("compare_bar");
}
}
}
SetTextMesssage("compare_bar");
getSimilarImages("所有图片的比较已完成");
updateDataGridViewer();
MessageBox.Show("所有图片的比较已完成!");
}
else
{
// 使用子线程来进行读取图片操作
for (int i = 0; i < this.thread_num; i++)
{
int start_index = i * all_images_group.Count / thread_num;
sub_num = (i + 1 == thread_num ? all_images_group.Count - i * all_images_group.Count / thread_num : all_images_group.Count / thread_num);
List <String> sub_images_group = this.all_images_group.GetRange(start_index, sub_num);
Thread image_hashval_thread = new Thread(new ParameterizedThreadStart(getAllImagesHashVal));
image_hashval_thread.Start(sub_images_group);
}
// 完成读取后的操作
Thread finish_readimg_thread = new Thread(FinishReadImg);
finish_readimg_thread.Start();
// 使用子线程来进行图片比较操作
for (int i = 0; i < this.thread_num; i++)
{
Thread compare_thread = new Thread(new ParameterizedThreadStart(ComputeSimilar));
compare_thread.Start(i);
}
// 完成比较后的操作
Thread finish_compare_thread = new Thread(FinishCompareData);
finish_compare_thread.IsBackground = true;
finish_compare_thread.Start();
}
}
}
