Merge remote-tracking branch 'origin/main'

.gitignore

@@ -1,3 +1,2 @@
-result/
 .idea/
 .vscode/

bm_struct_array.json

@@ -1,272 +1 @@
-[
+[{"code": 1, "type": "250x1450", "x": 945, "y": 0, "center": 351, "w": 1450, "h": 250, "angle": "0"}, {"code": 2, "type": "300x300", "x": 923, "y": 0, "center": 754, "w": 300, "h": 300, "angle": "0"}, {"code": 3, "type": "501x500", "x": 1638, "y": 0, "center": 1054, "w": 500, "h": 501, "angle": "0"}, {"code": 4, "type": "250x648", "x": 717, "y": 0, "center": 1149, "w": 648, "h": 250, "angle": "0"}, {"code": 5, "type": "250x250", "x": 1337, "y": 0, "center": 1543, "w": 250, "h": 250, "angle": "0"}, {"code": 6, "type": "249x249", "x": 1780, "y": 0, "center": 1750, "w": 249, "h": 249, "angle": "0"}, {"code": 7, "type": "400x399", "x": 549, "y": 0, "center": 1955, "w": 399, "h": 400, "angle": "0"}, {"code": 8, "type": "300x302", "x": 1143, "y": 0, "center": 2159, "w": 302, "h": 300, "angle": "0"}, {"code": 9, "type": "300x302", "x": 1745, "y": 0, "center": 2157, "w": 302, "h": 300, "angle": "0"}, {"code": 10, "type": "248x1447", "x": 2939, "y": 0, "center": 345, "w": 1447, "h": 248, "angle": "0"}, {"code": 11, "type": "298x297", "x": 2947, "y": 0, "center": 747, "w": 297, "h": 298, "angle": "0"}, {"code": 12, "type": "499x499", "x": 3640, "y": 0, "center": 1040, "w": 499, "h": 499, "angle": "0"}, {"code": 13, "type": "245x648", "x": 2743, "y": 0, "center": 1146, "w": 648, "h": 245, "angle": "0"}, {"code": 14, "type": "247x247", "x": 3338, "y": 0, "center": 1550, "w": 247, "h": 247, "angle": "0"}, {"code": 15, "type": "246x247", "x": 3747, "y": 0, "center": 1757, "w": 247, "h": 246, "angle": "0"}, {"code": 16, "type": "398x392", "x": 2548, "y": 0, "center": 1955, "w": 392, "h": 398, "angle": "0"}, {"code": 17, "type": "300x293", "x": 3143, "y": 0, "center": 2147, "w": 293, "h": 300, "angle": "0"}, {"code": 18, "type": "298x297", "x": 3750, "y": 0, "center": 2144, "w": 297, "h": 298, "angle": "0"}, {"code": 19, "type": "245x1447", "x": 4940, "y": 0, "center": 344, "w": 1447, "h": 245, "angle": "0"}, {"code": 20, "type": "295x300", "x": 4924, "y": 0, "center": 743, "w": 300, "h": 295, "angle": "0"}, {"code": 21, "type": "498x495", "x": 5646, "y": 0, "center": 1030, "w": 495, "h": 498, "angle": "0"}, {"code": 22, "type": "245x648", "x": 4726, "y": 0, "center": 1150, "w": 648, "h": 245, "angle": "0"}, {"code": 23, "type": "245x246", "x": 5296, "y": 0, "center": 1541, "w": 246, "h": 245, "angle": "0"}, {"code": 24, "type": "245x245", "x": 5741, "y": 0, "center": 1735, "w": 245, "h": 245, "angle": "0"}, {"code": 25, "type": "398x392", "x": 4545, "y": 0, "center": 1955, "w": 392, "h": 398, "angle": "0"}, {"code": 26, "type": "298x296", "x": 5141, "y": 0, "center": 2142, "w": 296, "h": 298, "angle": "0"}, {"code": 27, "type": "297x295", "x": 5740, "y": 0, "center": 2146, "w": 295, "h": 297, "angle": "0"}]
-  {
-    "code": "1",
-    "type": "250x1450",
-    "x": "196.0",
-    "y": 0,
-    "center": "351",
-    "w": "1450",
-    "h": "250",
-    "angle": "0\u00b0"
-  },
-  {
-    "code": "2",
-    "type": "300x300",
-    "x": "174.0",
-    "y": 0,
-    "center": "754",
-    "w": "300",
-    "h": "300",
-    "angle": "0\u00b0"
-  },
-  {
-    "code": "3",
-    "type": "501x500",
-    "x": "889.5",
-    "y": 0,
-    "center": "1054.5",
-    "w": "500",
-    "h": "501",
-    "angle": "0\u00b0"
-  },
-  {
-    "code": "4",
-    "type": "250x648",
-    "x": "-32.0",
-    "y": 0,
-    "center": "1149",
-    "w": "648",
-    "h": "250",
-    "angle": "0\u00b0"
-  },
-  {
-    "code": "5",
-    "type": "250x250",
-    "x": "588.0",
-    "y": 0,
-    "center": "1543",
-    "w": "250",
-    "h": "250",
-    "angle": "0\u00b0"
-  },
-  {
-    "code": "6",
-    "type": "249x249",
-    "x": "1031.5",
-    "y": 0,
-    "center": "1750.5",
-    "w": "249",
-    "h": "249",
-    "angle": "0\u00b0"
-  },
-  {
-    "code": "7",
-    "type": "400x399",
-    "x": "-199.5",
-    "y": 0,
-    "center": "1955",
-    "w": "399",
-    "h": "400",
-    "angle": "0\u00b0"
-  },
-  {
-    "code": "8",
-    "type": "300x302",
-    "x": "394.0",
-    "y": 0,
-    "center": "2159",
-    "w": "302",
-    "h": "300",
-    "angle": "0\u00b0"
-  },
-  {
-    "code": "9",
-    "type": "300x302",
-    "x": "996.0",
-    "y": 0,
-    "center": "2157",
-    "w": "302",
-    "h": "300",
-    "angle": "0\u00b0"
-  },
-  {
-    "code": "10",
-    "type": "248x1447",
-    "x": "2190.0",
-    "y": 0,
-    "center": "345",
-    "w": "1447",
-    "h": "248",
-    "angle": "0\u00b0"
-  },
-  {
-    "code": "11",
-    "type": "298x297",
-    "x": "2198.5",
-    "y": 0,
-    "center": "747",
-    "w": "297",
-    "h": "298",
-    "angle": "0\u00b0"
-  },
-  {
-    "code": "12",
-    "type": "499x499",
-    "x": "2891.0",
-    "y": 0,
-    "center": "1040.5",
-    "w": "499",
-    "h": "499",
-    "angle": "0\u00b0"
-  },
-  {
-    "code": "13",
-    "type": "245x648",
-    "x": "1994.5",
-    "y": 0,
-    "center": "1146.5",
-    "w": "648",
-    "h": "245",
-    "angle": "0\u00b0"
-  },
-  {
-    "code": "14",
-    "type": "247x247",
-    "x": "2589.5",
-    "y": 0,
-    "center": "1550.5",
-    "w": "247",
-    "h": "247",
-    "angle": "0\u00b0"
-  },
-  {
-    "code": "15",
-    "type": "246x247",
-    "x": "2998.5",
-    "y": 0,
-    "center": "1757",
-    "w": "247",
-    "h": "246",
-    "angle": "0\u00b0"
-  },
-  {
-    "code": "16",
-    "type": "398x392",
-    "x": "1799.5",
-    "y": 0,
-    "center": "1955",
-    "w": "392",
-    "h": "398",
-    "angle": "0\u00b0"
-  },
-  {
-    "code": "17",
-    "type": "300x293",
-    "x": "2394.5",
-    "y": 0,
-    "center": "2147",
-    "w": "293",
-    "h": "300",
-    "angle": "0\u00b0"
-  },
-  {
-    "code": "18",
-    "type": "298x297",
-    "x": "3001.5",
-    "y": 0,
-    "center": "2144",
-    "w": "297",
-    "h": "298",
-    "angle": "0\u00b0"
-  },
-  {
-    "code": "19",
-    "type": "245x1447",
-    "x": "4191.5",
-    "y": 0,
-    "center": "344.5",
-    "w": "1447",
-    "h": "245",
-    "angle": "0\u00b0"
-  },
-  {
-    "code": "20",
-    "type": "295x300",
-    "x": "4175.0",
-    "y": 0,
-    "center": "743.5",
-    "w": "300",
-    "h": "295",
-    "angle": "0\u00b0"
-  },
-  {
-    "code": "21",
-    "type": "498x495",
-    "x": "4897.5",
-    "y": 0,
-    "center": "1030",
-    "w": "495",
-    "h": "498",
-    "angle": "0\u00b0"
-  },
-  {
-    "code": "22",
-    "type": "245x648",
-    "x": "3977.0",
-    "y": 0,
-    "center": "1150.5",
-    "w": "648",
-    "h": "245",
-    "angle": "0\u00b0"
-  },
-  {
-    "code": "23",
-    "type": "245x246",
-    "x": "4547.5",
-    "y": 0,
-    "center": "1541.5",
-    "w": "246",
-    "h": "245",
-    "angle": "0\u00b0"
-  },
-  {
-    "code": "24",
-    "type": "245x245",
-    "x": "4992.5",
-    "y": 0,
-    "center": "1735.5",
-    "w": "245",
-    "h": "245",
-    "angle": "0\u00b0"
-  },
-  {
-    "code": "25",
-    "type": "398x392",
-    "x": "3796.5",
-    "y": 0,
-    "center": "1955",
-    "w": "392",
-    "h": "398",
-    "angle": "0\u00b0"
-  },
-  {
-    "code": "26",
-    "type": "298x296",
-    "x": "4392.5",
-    "y": 0,
-    "center": "2142",
-    "w": "296",
-    "h": "298",
-    "angle": "0\u00b0"
-  },
-  {
-    "code": "27",
-    "type": "297x295",
-    "x": "4991.5",
-    "y": 0,
-    "center": "2146.5",
-    "w": "295",
-    "h": "297",
-    "angle": "0\u00b0"
-  }
-]

config.ini

@@ -38,11 +38,11 @@ cloud_need_points_size = 600000
 save_cload = true
 
 [sys]
-fake = false
+fake = true
 camera_cap_fake = true
 lidar_cap_fake = true
 npu_fake = true
-conners_detect_fake = false
+conners_detect_fake = true
-fake_image_fpath = ./result/test_1/ep_100000_count_600000/output.jpg
+fake_image_fpath = ./result/hy_1/output.jpg
-fake_lidar_fpath = ./result/test_1/ep_100000_count_600000/output.ply
+fake_lidar_fpath = ./result/hy_1/output.ply
 

detect.py

@@ -182,6 +182,7 @@ def init_image_framework_sdk():
         # 加载C++库
         current_file_dir = os.path.dirname(os.path.abspath(__file__))
         image_framework_sdk = CDLL(os.path.join(current_file_dir, f'./image_framework.dll'))
+        print(f"[image_framework_sdk] ====== [{image_framework_sdk}]")
         print("Load Image framework sdk success")
     except Exception as e:
         print(f"Load Image framework sdk failed: {str(e)}")
@@ -236,7 +237,7 @@ if __name__ == '__main__':
         raise RuntimeError(f"设置回调函数始设置失败, 错误码: {ret}")
 
 
-    dataPath = "./result/hy_1" # 数据路径
+    dataPath = "./result" # 数据路径
     data_img_path = None # 检测的图片路径
     data_detect_res_save_path = None # 检测结果的保存路径
     # 遍历目录

excel_point_to_bm_json_.py

@@ -22,12 +22,18 @@ x_min, x_max = float('inf'), float('-inf')
 y_min, y_max = float('inf'), float('-inf')
 
 
-x_max_original = 0
+x_center_max = 0 # 在右测坐标系中。所有预埋件中心点的x坐标最大的值
+x_center_max_w = 0
+x_center_max_h = 0
 for index, row in df.iloc[2:30].iterrows():
-    original_x = row[col('K')] - row[col('D')] / 2
+    original_x_center = row[col('K')]
-    if(original_x > x_max_original):
+    if(original_x_center > x_center_max):
-        x_max_original = original_x
+        x_center_max = original_x_center
-
+        x_center_max_w = row[col('D')]
+        x_center_max_h = row[col('E')]
+print(f"x_center_max_original={x_center_max}")
+# 以为预埋件中心点的x最大的矩形的左下角作为坐标原点
+x_center_max_left_bottom = x_center_max + x_center_max_w / 2
 
 bm_struct_array = []
 
@@ -35,14 +41,22 @@ for index, row in df.iloc[2:30].iterrows():
     # 打印B列和C列的值
     print(f"行 {index+2} -> A列-编号: {row[col('A')]},  D列-测量宽度: {row[col('D')]}, E列-测量高度: {row[col('E')]}，K列-测量中心x: {row[col('K')]}, L列-测量中心y: {row[col('L')]}")
 
-    # 转换x坐标
+    # 使用新的中心点，之后，x坐标需要转换
-    x_original = row[col('K')]
+    x_center_original = row[col('K')]
-    x = x_max_original - x_original - row[col('D')] / 2
+    center_x =(-x_center_original) + x_center_max_left_bottom + 350
-    y = row[col('L')] - row[col('E')] / 2
+    # center_x = -x_center_original
-
-    # 转换中心点坐标
-    center_x = x_max_original - x_original
     center_y = row[col('L')]
+    width = row[col('D')]
+    height = row[col('E')]
+    # 左上角
+    x = center_x - width / 2
+    # 左上角
+    y = center_y + height / 2
+    # 左下角
+    x_left_bottom = center_x - width / 2
+    # 左下角
+    y_left_bottom = center_y - height / 2
+
 
     # [{
     #     "code": "PT001",
@@ -55,27 +69,21 @@ for index, row in df.iloc[2:30].iterrows():
     #     "angle": "90\""
     # },
     bm_struct_array.append({
-        "code": str(row[col('A')]),
+        "code": int(row[col('A')]),
-        "type": f"{str(row[col('E')])}x{str(row[col('D')])}",# w x h
+        "type": f"{height}x{width}",# h x w
-        "x": str(center_x),
+        "x": int(center_x),
         "y": 0,
-        "center": str(center_y),
+        "center": int(center_y),
-        "w": str(row[col('D')]),
+        "w":width,
-        "h": str(row[col('E')]),
+        "h": height,
-        "angle" : "0°"
+        "angle" : "0"
     })
 
     # 画出中心点
     ax.scatter(center_x, center_y, color='red', marker='o', s=10)
 
-    # 更新边界
-    x_min = min(x_min, x)
-    x_max = max(x_max, x + row[col('D')])
-    y_min = min(y_min, y)
-    y_max = max(y_max, y + row[col('E')])
-
     # 绘制矩形
-    rect = Rectangle((x, y), row[col('D')], row[col('E')], linewidth=1, edgecolor='r', facecolor='none')
+    rect = Rectangle((x_left_bottom, y_left_bottom),width, height, linewidth=1, edgecolor='r', facecolor='none')
     ax.add_patch(rect)
 
     # 在矩形中心绘制编号（A列）
@@ -87,21 +95,21 @@ for index, row in df.iloc[2:30].iterrows():
 
     # 在矩形上边绘制宽度（D列）
     ax.text(
-        x + row[col('D')] / 2, y + row[col('E')], str(row[col('D')]),
+        x + row[col('D')] / 2, y_left_bottom + row[col('E')], str(row[col('D')]),
         ha='center', va='bottom',
         fontsize=6, color='green'  # 宽度字体大小为10，颜色为绿色
     )
 
     # 在矩形右边绘制高度（E列）
     ax.text(
-        x + row[col('D')], y + row[col('E')] / 2, str(row[col('E')]),
+        x + width, y_left_bottom + height / 2, height,
         ha='left', va='center',
         fontsize=6, color='red'  # 高度字体大小为10，颜色为红色
     )
 
-# 设置坐标轴的范围，外扩100左右
+# 设置坐标轴的范围
-ax.set_xlim(x_min, x_max )  # 留出一些边距
+# ax.set_xlim(x_min, x_max )  # 留出一些边距
-ax.set_ylim(y_min, y_max )  # 留出一些边距
+# ax.set_ylim(y_min, y_max )  # 留出一些边距
 
 # 设置坐标轴的比例
 ax.set_aspect('equal')

points.txt

@@ -1,27 +1,27 @@
-[(4366.0, 226.0), (5816.0, 226.0), (5816.0, 476.0), (4366.0, 476.0)]
+[[4366.0, 226.0], [5816.0, 226.0], [5816.0, 476.0], [4366.0, 476.0]]
-[(4963.0, 604.0), (5263.0, 604.0), (5263.0, 904.0), (4963.0, 904.0)]
+[[4963.0, 604.0], [5263.0, 604.0], [5263.0, 904.0], [4963.0, 904.0]]
-[(4147.5, 804.0), (4647.5, 804.0), (4647.5, 1305.0), (4147.5, 1305.0)]
+[[4147.5, 804.0], [4647.5, 804.0], [4647.5, 1305.0], [4147.5, 1305.0]]
-[(4995.0, 1024.0), (5643.0, 1024.0), (5643.0, 1274.0), (4995.0, 1274.0)]
+[[4995.0, 1024.0], [5643.0, 1024.0], [5643.0, 1274.0], [4995.0, 1274.0]]
-[(4574.0, 1418.0), (4824.0, 1418.0), (4824.0, 1668.0), (4574.0, 1668.0)]
+[[4574.0, 1418.0], [4824.0, 1418.0], [4824.0, 1668.0], [4574.0, 1668.0]]
-[(4131.0, 1626.0), (4380.0, 1626.0), (4380.0, 1875.0), (4131.0, 1875.0)]
+[[4131.0, 1626.0], [4380.0, 1626.0], [4380.0, 1875.0], [4131.0, 1875.0]]
-[(5287.0, 1755.0), (5686.0, 1755.0), (5686.0, 2155.0), (5287.0, 2155.0)]
+[[5287.0, 1755.0], [5686.0, 1755.0], [5686.0, 2155.0], [5287.0, 2155.0]]
-[(4742.0, 2009.0), (5044.0, 2009.0), (5044.0, 2309.0), (4742.0, 2309.0)]
+[[4742.0, 2009.0], [5044.0, 2009.0], [5044.0, 2309.0], [4742.0, 2309.0]]
-[(4140.0, 2007.0), (4442.0, 2007.0), (4442.0, 2307.0), (4140.0, 2307.0)]
+[[4140.0, 2007.0], [4442.0, 2007.0], [4442.0, 2307.0], [4140.0, 2307.0]]
-[(2373.5, 221.0), (3820.5, 221.0), (3820.5, 469.0), (2373.5, 469.0)]
+[[2373.5, 221.0], [3820.5, 221.0], [3820.5, 469.0], [2373.5, 469.0]]
-[(2940.0, 598.0), (3237.0, 598.0), (3237.0, 896.0), (2940.0, 896.0)]
+[[2940.0, 598.0], [3237.0, 598.0], [3237.0, 896.0], [2940.0, 896.0]]
-[(2146.5, 791.0), (2645.5, 791.0), (2645.5, 1290.0), (2146.5, 1290.0)]
+[[2146.5, 791.0], [2645.5, 791.0], [2645.5, 1290.0], [2146.5, 1290.0]]
-[(2968.5, 1024.0), (3616.5, 1024.0), (3616.5, 1269.0), (2968.5, 1269.0)]
+[[2968.5, 1024.0], [3616.5, 1024.0], [3616.5, 1269.0], [2968.5, 1269.0]]
-[(2574.0, 1427.0), (2821.0, 1427.0), (2821.0, 1674.0), (2574.0, 1674.0)]
+[[2574.0, 1427.0], [2821.0, 1427.0], [2821.0, 1674.0], [2574.0, 1674.0]]
-[(2165.0, 1634.0), (2412.0, 1634.0), (2412.0, 1880.0), (2165.0, 1880.0)]
+[[2165.0, 1634.0], [2412.0, 1634.0], [2412.0, 1880.0], [2165.0, 1880.0]]
-[(3291.5, 1756.0), (3683.5, 1756.0), (3683.5, 2154.0), (3291.5, 2154.0)]
+[[3291.5, 1756.0], [3683.5, 1756.0], [3683.5, 2154.0], [3291.5, 2154.0]]
-[(2746.0, 1997.0), (3039.0, 1997.0), (3039.0, 2297.0), (2746.0, 2297.0)]
+[[2746.0, 1997.0], [3039.0, 1997.0], [3039.0, 2297.0], [2746.0, 2297.0]]
-[(2137.0, 1995.0), (2434.0, 1995.0), (2434.0, 2293.0), (2137.0, 2293.0)]
+[[2137.0, 1995.0], [2434.0, 1995.0], [2434.0, 2293.0], [2137.0, 2293.0]]
-[(372.0, 222.0), (1819.0, 222.0), (1819.0, 467.0), (372.0, 467.0)]
+[[372.0, 222.0], [1819.0, 222.0], [1819.0, 467.0], [372.0, 467.0]]
-[(962.0, 596.0), (1262.0, 596.0), (1262.0, 891.0), (962.0, 891.0)]
+[[962.0, 596.0], [1262.0, 596.0], [1262.0, 891.0], [962.0, 891.0]]
-[(142.0, 781.0), (637.0, 781.0), (637.0, 1279.0), (142.0, 1279.0)]
+[[142.0, 781.0], [637.0, 781.0], [637.0, 1279.0], [142.0, 1279.0]]
-[(986.0, 1028.0), (1634.0, 1028.0), (1634.0, 1273.0), (986.0, 1273.0)]
+[[986.0, 1028.0], [1634.0, 1028.0], [1634.0, 1273.0], [986.0, 1273.0]]
-[(616.5, 1419.0), (862.5, 1419.0), (862.5, 1664.0), (616.5, 1664.0)]
+[[616.5, 1419.0], [862.5, 1419.0], [862.5, 1664.0], [616.5, 1664.0]]
-[(172.0, 1613.0), (417.0, 1613.0), (417.0, 1858.0), (172.0, 1858.0)]
+[[172.0, 1613.0], [417.0, 1613.0], [417.0, 1858.0], [172.0, 1858.0]]
-[(1294.5, 1756.0), (1686.5, 1756.0), (1686.5, 2154.0), (1294.5, 2154.0)]
+[[1294.5, 1756.0], [1686.5, 1756.0], [1686.5, 2154.0], [1294.5, 2154.0]]
-[(746.5, 1993.0), (1042.5, 1993.0), (1042.5, 2291.0), (746.5, 2291.0)]
+[[746.5, 1993.0], [1042.5, 1993.0], [1042.5, 2291.0], [746.5, 2291.0]]
-[(148.0, 1998.0), (443.0, 1998.0), (443.0, 2295.0), (148.0, 2295.0)]
+[[148.0, 1998.0], [443.0, 1998.0], [443.0, 2295.0], [148.0, 2295.0]]

readme.md

@@ -1,7 +1 @@
-```pycon
+conda env create -f environment.yaml
-self.image_framework = ImageFramework()
-self.image_framework.signals.on_image_detect_result.connect(
-lambda data: self.image_result(data))
-self.image_framework.configure()
-self.image_framework.start()
-```

result/hy_1/roi_conners.txt

@@ -0,0 +1,64 @@
+6911
+3175
+7935
+3175
+7935
+4142
+6911
+4142
+5578
+3808
+6623
+3808
+6623
+4761
+5578
+4761
+2677
+5089
+5214
+5089
+5214
+6179
+2677
+6179
+2613
+2198
+4142
+2198
+4142
+3607
+2613
+3607
+73
+1746
+1314
+1746
+1314
+2799
+73
+2799
+52
+3066
+1092
+3066
+1092
+3997
+52
+3997
+4815
+1805
+5951
+1805
+5951
+2849
+4815
+2849
+6774
+1829
+7896
+1829
+7896
+2869
+6774
+2869

roi_conners.txt

@@ -1,24 +1,64 @@
-1131
+6911
-2007
+3175
-5900
+7935
-2007
+3175
-5900
+7935
-5376
+4142
-1131
+6911
-5376
+4142
-2004
+5578
-2958
+3808
-3142
+6623
-2958
+3808
-3142
+6623
-3948
+4761
-2004
+5578
-3948
+4761
-3887
+2677
-2919
+5089
-4839
+5214
-2919
+5089
-4839
+5214
-3902
+6179
-3887
+2677
-3902
+6179
+2613
+2198
+4142
+2198
+4142
+3607
+2613
+3607
+73
+1746
+1314
+1746
+1314
+2799
+73
+2799
+52
+3066
+1092
+3066
+1092
+3997
+52
+3997
+4815
+1805
+5951
+1805
+5951
+2849
+4815
+2849
+6774
+1829
+7896
+1829
+7896
+2869
+6774
+2869