勉强拍完了技术视频

QT.py

@@ -367,7 +367,7 @@ def save_result(self):
         else:
             for res in self.result:
                 f.write('GOAL_ID=%s;' % res[0])
-                f.write('GOAL_Radius%.1f\n' % (res[4] / res[1]))
+                f.write('GOAL_Radius=%.1f\n' % (res[4] / res[1]))
                 res[1] = res[2] = res[3] = res[4] = res[5] = 0
         f.write('END')
         print('    \33[0;32m第%s回合结果已保存\033[0m' % self.round)
@@ -455,11 +455,10 @@ def capture_camera(self, camera):
                 corners = np.matmul(corners, [[640, 0], [0, 480]])
                 corners = np.append(corners, [[1], [1], [1], [1]], axis=1)
                 transed, angle = corner.square_trans(Table_2D, corners)
-                np.mean([transed[i][0] for i in range(4)])
-                data.append(
-                    '%.1f' % (np.mean([transed[i][0] for i in range(4)]) / 10))  # x
-                data.append(
-                    '%.1f' % (np.mean([transed[i][1] for i in range(4)]) / 10))  # y
+                avgx = np.mean([transed[i][0] for i in range(4)])
+                avgy = np.mean([transed[i][1] for i in range(4)])
+                data.append('%.1f' % (avgx / 10))  # x
+                data.append('%.1f' % (avgy / 10))  # y
                 data.append('')  # radius
                 data.append('%.1f' % angle)  # angle
                 del corners
@@ -474,14 +473,14 @@ def capture_camera(self, camera):
                     corners = [bs[1], bs[3], bs[5], bs[7]]
                 corners = np.matmul(corners, [[640, 0], [0, 480]])
                 corners = np.append(corners, [[1], [1], [1], [1]], axis=1)
-                transed, angle = circle_fit.circle_trans(Circle_2D, corners, lined)
-                np.mean([transed[i][0] for i in range(4)])
-                data.append(
-                    '%.1f' % (np.mean([transed[i][0] for i in range(4)]) / 10))  # x
-                data.append(
-                    '%.1f' % (np.mean([transed[i][1] for i in range(4)]) / 10))  # y
-                data.append('')  # radius
-                data.append('%.1f' % angle)  # angle
+                transed = circle_fit.circle_trans(Circle_2D, corners)
+                avgx = np.mean([transed[i][0] for i in range(4)])
+                avgy = np.mean([transed[i][1] for i in range(4)])
+                radius = (avgx ** 2 + avgy ** 2) ** 0.5
+                data.append('')  # x
+                data.append('')  # y
+                data.append('%.1f' % (radius / 10))  # radius
+                data.append('')  # angle
                 del corners
 
         print("    \033[0;34m绘制预测中...\033[0m")
@@ -495,15 +494,20 @@ def capture_camera(self, camera):
         for data in datas:
             for res in self.result:
                 if data[0][0] == res[0]:  # 名称一致
-                    res[1] += float(data[0][1].strip('%')) / 100  # 置信度之和
                     if self.isSquare:
+                        if (float(data[1]) >= 55 or float(data[1]) <= 0 or float(data[2]) >= 55 or float(data[2]) <= 0):
+                            continue
+                        res[1] += float(data[0][1].strip('%')) / 100  # 置信度之和
                         res[2] += float(data[1]) * float(data[0]
                                                          [1].strip('%')) / 100  # x之和
                         res[3] += float(data[2]) * float(data[0]
                                                          [1].strip('%')) / 100  # y之和
                         res[5] += float(data[4]) * float(data[0]
                                                          [1].strip('%')) / 100  # a之和
                     else:
+                        if float(data[3]) >= 30:  # 错误识别
+                            continue
+                        res[1] += float(data[0][1].strip('%')) / 100  # 置信度之和
                         res[4] += float(data[3]) * float(data[0]
                                                          [1].strip('%')) / 100  # r之和
 

circle_fit.py

@@ -82,36 +82,39 @@ def circle_line(origin, thresed, S_thre=(100000, 600000)):
     contours, _ = cv2.findContours(thresed, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
     top = []; bottle = []; right = []; left = []; center = []
     Circle_2D = []
+    last_longest = 4
+    des_ell = tuple()
     for cnt in contours:
-        if len(cnt) > 0:
+        if len(cnt) > last_longest:  # 确保输出点数最多（且面积不超标）的椭圆
             ell=cv2.fitEllipse(cnt) # 返回椭圆所在的矩形框# 函数返回值为：椭圆的中心坐标，长短轴长度（2a，2b），旋转角度
             S2 =math.pi*ell[1][0]*ell[1][1] # 椭圆面积
-            # if S2>= S_thre[0] and S2 <= S_thre[1]: # 过滤面积小的
-            des_ell = ell
-
-            top_x = ell[0][0] - 0.5 * ell[1][0] * math.cos(math.radians(ell[2]))
-            top_y = ell[0][1] - 0.5 * ell[1][0] * math.sin(math.radians(ell[2]))
-            bottle_x = ell[0][0] + 0.5 * ell[1][0] * math.cos(math.radians(ell[2]))
-            bottle_y = ell[0][1] + 0.5 * ell[1][0] * math.sin(math.radians(ell[2]))
-
-            right_x = ell[0][0] + 0.5 * ell[1][1] * math.sin(math.radians(ell[2]))
-            right_y = ell[0][1] - 0.5 * ell[1][1] * math.cos(math.radians(ell[2]))
-            left_x = ell[0][0] - 0.5 * ell[1][1] * math.sin(math.radians(ell[2]))
-            left_y = ell[0][1] + 0.5 * ell[1][1] * math.cos(math.radians(ell[2]))
+            if S2>= S_thre[0] and S2 <= S_thre[1]: # 过滤面积小的
+                last_longest = len(cnt)
+                des_ell = ell
+
+                top_x = ell[0][0] - 0.5 * ell[1][0] * math.cos(math.radians(ell[2]))
+                top_y = ell[0][1] - 0.5 * ell[1][0] * math.sin(math.radians(ell[2]))
+                bottle_x = ell[0][0] + 0.5 * ell[1][0] * math.cos(math.radians(ell[2]))
+                bottle_y = ell[0][1] + 0.5 * ell[1][0] * math.sin(math.radians(ell[2]))
+
+                right_x = ell[0][0] + 0.5 * ell[1][1] * math.sin(math.radians(ell[2]))
+                right_y = ell[0][1] - 0.5 * ell[1][1] * math.cos(math.radians(ell[2]))
+                left_x = ell[0][0] - 0.5 * ell[1][1] * math.sin(math.radians(ell[2]))
+                left_y = ell[0][1] + 0.5 * ell[1][1] * math.cos(math.radians(ell[2]))
 
-            top = (int(top_x), int(top_y))
-            bottle = (int(bottle_x), int(bottle_y))
-            right = (int(right_x), int(right_y))
-            left = (int(left_x), int(left_y))
-            center = (int(ell[0][0]), int(ell[0][1]))
-
-            origin = cv2.ellipse(origin, des_ell, (0, 255, 0), 2) # 绘制椭圆
-
-            drawpoi(origin, top)
-            drawpoi(origin, bottle)
-            drawpoi(origin, right)
-            drawpoi(origin, left)
-            drawpoi(origin, center)
+                top = (int(top_x), int(top_y))
+                bottle = (int(bottle_x), int(bottle_y))
+                right = (int(right_x), int(right_y))
+                left = (int(left_x), int(left_y))
+                center = (int(ell[0][0]), int(ell[0][1]))
+
+    origin = cv2.ellipse(origin, des_ell, (0, 255, 0), 2) # 绘制椭圆
+
+    drawpoi(origin, top)
+    drawpoi(origin, bottle)
+    drawpoi(origin, right)
+    drawpoi(origin, left)
+    drawpoi(origin, center)
 
             # rate = ell[1][1]/ell[1][0]
             # elif S2< S_thre[1]:
@@ -137,7 +140,7 @@ def circle_desk(num, x, canny, hough):
 
     thresed = corner.thres(img, x)
     thresed_new = corner.remove_small_objects(thresed)
-    lined, _, Circle_2D = circle_line(img, thresed_new, [150000, 600000])
+    lined, _, Circle_2D = circle_line(img, thresed_new, [100000, 600000])
     # affine_table_2D = np.float32([[0,0],[0,550],[550,0],[550,550]])
     # M = cv2.getPerspectiveTransform(Table_2D,affine_table_2D)
     # marked = cv2.warpPerspective(lined,M,(550,550)) # Perspective_Transformation
@@ -161,8 +164,6 @@ def circle_trans(Cicle_2D: '上下右左', points: '物体底部四点', lined_i
     a = [0 for i in range(4)]
     for i in range(4):
         a[i] = (int(transed_points[i][0]), int(transed_points[i][1]))
-    angle = np.degrees(np.arccos(
-        (a[0][0] - a[0][1]) / (((a[0][0] - a[0][1])**2 + (a[1][0] - a[1][1])**2) ** 0.5)))
 
     if len(lined_img):
         # Perspective_Transformation
@@ -173,15 +174,6 @@ def circle_trans(Cicle_2D: '上下右左', points: '物体底部四点', lined_i
         cv2.line(transed, a[2], a[3], (0, 255, 0), 1)
         cv2.imshow('perspective', transed)
 
-    return transed_points, angle
-
-
-# if __name__ == '__main__':
-#     ima = cv2.imread("JPEGImages/1.jpg", 3)
-#     out, top, bottle, right, left = my_fun(ima)
-#     cv2.imshow("output1.jpg",out)
-#     cv2.waitKey(0)
-
-
+    return transed_points
 
 

data1.txt

@@ -1,6 +1,6 @@
-red_low = 180
-red_high = 210
-green_low = 180
-green_high = 210
-blue_low = 180
-blue_high = 210
+red_low = 185
+red_high = 215
+green_low = 185
+green_high = 215
+blue_low = 185
+blue_high = 215

debugger.py

@@ -255,8 +255,9 @@ def setting_2(self):
         ho[2] = self.lineEdit_12.text()
         img = corner.thres(self.img, self.x)
         thresed = corner.remove_small_objects(img)
-        # edges = circle_fit.circle_canny(self.img, ca)
+        # edges = corner.square_canny(thresed, ca)
         # cv2.imshow('edges', edges)
+        # lined, Table_2D = corner.square_line(self.img, edges, ho)
         lined, _, Circle_2D = circle_fit.circle_line(self.img, thresed)
         cv2.imshow('lines', lined)
 

test.py

@@ -0,0 +1,21 @@
+from yolo6D.Predict import *
+
+if __name__ == "__main__":
+    name = 'ZB008'
+    img_path = '1.jpg'
+    img = cv2.imread(img_path)
+    model = dn('yolo6D/yolo-pose.cfg')
+    model.load_weights('weights/' + name + '.weights')
+    boxes = detect(name, model, img_path)
+    best_conf_est = -1
+    for j in range(len(boxes)):
+        if (boxes[j][18] > best_conf_est):
+            box_pr = boxes[j]
+            best_conf_est = boxes[j][18]
+
+    bss = [np.array(np.reshape(box_pr[:18], [9, 2]), dtype='float32')]
+    strs = []
+    strs.append(name)
+    strs.append(str(int(best_conf_est.numpy() * 100)) + '%')
+    strss = [strs]
+    draw_predict(bss, strss, img, -1)

东南大学-LabVIEW-R1.txt

@@ -1,2 +1,5 @@
 START
-GOAL_ID=ZA001;
+GOAL_ID=ZA001;GOAL_X=12.5;GOAL_Y=46.0;GOAL_Angle=133.8
+GOAL_ID=ZA004;GOAL_X=34.6;GOAL_Y=28.3;GOAL_Angle=83.1
+GOAL_ID=ZB008;GOAL_X=23.2;GOAL_Y=39.2;GOAL_Angle=154.3
+END

东南大学-LabVIEW-R2.txt

@@ -1,5 +1,5 @@
 START
-GOAL_ID=copico;GOAL_X=-117.7;GOAL_Y=545.0;GOAL_Angle=
-GOAL_ID=copico;GOAL_X=39.9;GOAL_Y=-179.4;GOAL_Angle=
-GOAL_ID=copico;GOAL_X=-125.7;GOAL_Y=-229.4;GOAL_Angle=
+GOAL_ID=ZA001;GOAL_Radius30.8
+GOAL_ID=ZA004;GOAL_Radius27.4
+GOAL_ID=ZB008;GOAL_Radius48.4
 END