Merge branch 'dev' of

http://gogs.seec.seecoder.cn/ZhaoFengShan/PoseCorrection into dev

backend_refactor/service/video_analyzer.py

@@ -76,6 +76,293 @@ class BaseVideoAnalyzer:
             raise e
 
 
+def angle1(v1, v2):
+    dx1 = v1[2] - v1[0]
+    dy1 = v1[3] - v1[1]
+    angle1 = float(math.atan2(dy1, dx1))
+    angle2 = abs(round(angle1 * 180.0 / math.pi, 2))
+    return angle2
+
+
+# calculate the angle between 3 points under the coordinates
+# params: list, item [x,y]
+# return: the angle value of b
+def cal_angle(point_a, point_b, point_c):
+    a_x, b_x, c_x = point_a[0], point_b[0], point_c[0]
+    a_y, b_y, c_y = point_a[1], point_b[1], point_c[1]
+    a_z, b_z, c_z = 0, 0, 0
+    #  m=(x1,y1,z1), n=(x2,y2,z2)
+    x1, y1, z1 = (a_x - b_x), (a_y - b_y), (a_z - b_z)
+    x2, y2, z2 = (c_x - b_x), (c_y - b_y), (c_z - b_z)
+
+    cos_b = (x1 * x2 + y1 * y2 + z1 * z2) / (
+            math.sqrt(x1 ** 2 + y1 ** 2 + z1 ** 2) * (math.sqrt(x2 ** 2 + y2 ** 2 + z2 ** 2)))
+    B = math.degrees(math.acos(cos_b))
+    return round(B, 2)
+
+
+def analyse_npy_crunch_side(data):
+    result = {}
+
+    print(len(data))
+    assert len(data) == 25, "error"
+
+    nose_x = data[0][0]
+    nose_y = data[0][1]
+    shoulder_r_x = data[2][0]
+    shoulder_r_y = data[2][1]
+    elbow_r_x = data[3][0]
+    elbow_r_y = data[3][1]
+    wrist_r_x = data[4][0]
+    wrist_r_y = data[4][1]
+
+    hip_r_x = data[9][0]
+    hip_r_y = data[9][1]
+    knee_r_x = data[10][0]
+    knee_r_y = data[10][1]
+    neck_x = data[1][0]
+    neck_y = data[1][1]
+    ankle_r_x = data[11][0]
+    ankle_r_y = data[11][1]
+    leg_heigh = data[11][1]
+    neck_hip_angle = round(angle1([neck_x, neck_y, hip_r_x, hip_r_y], [0, 0, 0, -1]), 2)
+    nose_neck_angle = round(angle1([nose_x, nose_y, neck_x, neck_y], [0, 0, 0, -1]), 2)
+    hip_knee_angle = round(angle1([hip_r_x, hip_r_y, knee_r_x, knee_r_y], [0, 0, 0, -1]), 2)
+    knee_ankle_angle = round(angle1([knee_r_x, knee_r_y, ankle_r_x, ankle_r_y], [0, 0, 0, -1]), 2)
+    result["neck_hip_angle"] = neck_hip_angle
+    result["nose_neck_angle"] = nose_neck_angle
+    result["hip_knee_angle"] = hip_knee_angle
+    result["knee_ankle_angle"] = knee_ankle_angle
+    return result
+
+
+def analyse_npy_side_pingban(data):
+    result = {}
+    assert len(data) >= 15, "error"
+
+    shoulder_r_x = data[2][0]
+    shoulder_r_y = data[2][1]
+    elbow_r_x = data[3][0]
+    elbow_r_y = data[3][1]
+    wrist_r_x = data[4][0]
+    wrist_r_y = data[4][1]
+
+    hip_r_x = data[9][0]
+    hip_r_y = data[9][1]
+    knee_r_x = data[10][0]
+    knee_r_y = data[10][1]
+    neck_x = data[1][0]
+    neck_y = data[1][1]
+    ankle_r_x = data[11][0]
+    ankle_r_y = data[11][1]
+    bigToe_r_x = data[22][0]
+    bigToe_r_y = data[22][1]
+    knee_ankle_angle = round(angle1([knee_r_x, knee_r_y, ankle_r_x, ankle_r_y], [0, 0, 0, -1]), 2)
+    leg_heigh = data[11][1]
+    neck_hip_angle = round(angle1([neck_x, neck_y, hip_r_x, hip_r_y], [0, 0, 0, -1]), 2)
+    hip_knee_angle = round(angle1([hip_r_x, hip_r_y, knee_r_x, knee_r_y], [0, 0, 0, -1]), 2)
+    s_e_angle = round(angle1([shoulder_r_x, shoulder_r_y, elbow_r_x, elbow_r_y], []), 2)
+    e_w_angle = round(angle1([elbow_r_x, elbow_r_y, wrist_r_x, wrist_r_y], []), 2)
+    hip_heigh = hip_r_y
+
+    result["knee_ankle_angle"] = knee_ankle_angle
+    result["leg_heigh"] = leg_heigh
+    result["neck_hip_angle"] = neck_hip_angle
+    result["hip_knee_angle"] = hip_knee_angle
+    result["hip_heigh"] = hip_heigh
+    result["s_e_angle"] = s_e_angle
+    result["e_w_angle"] = e_w_angle
+
+    # print(npy_side)
+    return result
+
+
+def analyse_npy_side_jump(data):
+    result = {}
+
+    assert len(data) == 25, "error"
+
+    # should-elbow-wrist r2-3-4 l5-6-7
+    # neck-hip-knee r1-9-10 l1-12-13
+    # hip-knee-ankle r9-10-11 l12-13-14
+    # knee-ankle-bigToe r10-11-22 l13-14-19
+    result["elbow_right_angle"] = cal_angle(data[2], data[3], data[4])
+    result["elbow_left_angle"] = cal_angle(data[5], data[6], data[7])
+    result["hip_right_angle"] = cal_angle(data[1], data[9], data[10])
+    result["hip_left_angle"] = cal_angle(data[1], data[12], data[13])
+    result["knee_right_angle"] = cal_angle(data[9], data[10], data[11])
+    result["knee_left_angle"] = cal_angle(data[12], data[13], data[14])
+    result["ankle_right_angle"] = cal_angle(data[10], data[11], data[12])
+    result["ankle_left_angle"] = cal_angle(data[13], data[14], data[19])
+    result["leg_heigh"] = data[11][1]  # ankle
+    result["hip_heigh"] = data[9][1]  # hip
+    result["wrist_heigh"] = data[4][1]
+    result["neck_heigh"] = data[1][1]
+
+    # knee_ankle_angle = round(angle1([knee_r_x, knee_r_y, ankle_r_x, ankle_r_y], [0, 0, 0, -1]), 2)
+    # neck_hip_angle = round(angle1([neck_x, neck_y, hip_r_x, hip_r_y], [0, 0, 0, -1]), 2)
+    # hip_knee_angle = round(angle1([hip_r_x, hip_r_y, knee_r_x, knee_r_y], [0, 0, 0, -1]), 2)
+    # hip_heigh = hip_r_y
+    # result["knee_ankle_angle"] = knee_ankle_angle
+    # result["leg_heigh"] = leg_heigh
+    # result["neck_hip_angle"] = neck_hip_angle
+    # result["hip_knee_angle"] = hip_knee_angle
+    # result["hip_heigh"] = hip_heigh
+
+    return result
+
+
+def analyse_npy_side_gaotaitui(data):
+    result = {}
+
+    assert len(data) == 25, "error"
+    # print(data)
+    hip_r_x = data[9][0]
+    hip_r_y = data[9][1]
+    knee_r_x = data[10][0]
+    knee_r_y = data[10][1]
+
+    hip_l_x = data[12][0]
+    hip_l_y = data[12][1]
+    knee_l_x = data[13][0]
+    knee_l_y = data[13][1]
+    # print(head_forward_level)
+    # upper part of body
+    up_risk_level = ""
+    up_state = ""
+    neck_x = data[1][0]
+    neck_y = data[1][1]
+    ankle_r_x = data[11][0]
+    ankle_r_y = data[11][1]
+    ankle_l_x = data[14][0]
+    ankle_l_y = data[14][1]
+    knee_ankle_r_angle = round(angle1([knee_r_x, knee_r_y, ankle_r_x, ankle_r_y], [0, 0, 0, -1]), 2)  # ϥ�ǵ���
+    knee_ankle_l_angle = round(angle1([knee_l_x, knee_l_y, ankle_l_x, ankle_l_y], [0, 0, 0, -1]), 2)  # ϥ�ǵ���
+
+    hip_knee_r_angle = round(angle1([hip_r_x, hip_r_y, knee_r_x, knee_r_y], [0, 0, 0, -1]), 2)
+    hip_knee_l_angle = round(angle1([hip_l_x, hip_l_y, knee_l_x, knee_l_y], [0, 0, 0, -1]), 2)
+    neck_hip_angle = round(angle1([neck_x, neck_y, hip_r_x, hip_r_y], [0, 0, 0, -1]), 2)
+    # hip_knee_angle=round(angle1([hip_r_x, hip_r_y,knee_r_x, knee_r_y], [0, 0, 0, -1]), 2)
+    hip_heigh = hip_r_y
+
+    result["knee_ankle_r_angle"] = knee_ankle_r_angle
+    result["knee_ankle_l_angle"] = knee_ankle_l_angle
+    result["hip_knee_r_angle"] = hip_knee_r_angle
+    result["hip_knee_l_angle"] = hip_knee_l_angle
+    result["r_d"] = abs(0 - float(hip_knee_r_angle) + float(knee_ankle_r_angle))
+    result["l_d"] = abs(0 + float(knee_ankle_l_angle) - float(hip_knee_l_angle))
+    return result
+
+
+def analyse_npy_side_shendun(data):
+    result = {}
+    assert len(data) == 25, "data length must be 25."
+    hip_r_x = data[9][0]
+    hip_r_y = data[9][1]
+    knee_r_x = data[10][0]
+    knee_r_y = data[10][1]
+
+    hip_l_x = data[12][0]
+    hip_l_y = data[12][1]
+    knee_l_x = data[13][0]
+    knee_l_y = data[13][1]
+    # print(head_forward_level)
+    # upper part of body
+    up_risk_level = ""
+    up_state = ""
+    neck_x = data[1][0]
+    neck_y = data[1][1]
+    ankle_r_x = data[11][0]
+    ankle_r_y = data[11][1]
+    ankle_l_x = data[14][0]
+    ankle_l_y = data[14][1]
+    knee_ankle_r_angle = round(angle1([knee_r_x, knee_r_y, ankle_r_x, ankle_r_y], [0, 0, 0, -1]), 2)
+    knee_ankle_l_angle = round(angle1([knee_l_x, knee_l_y, ankle_l_x, ankle_l_y], [0, 0, 0, -1]), 2)
+
+    hip_knee_r_angle = round(angle1([hip_r_x, hip_r_y, knee_r_x, knee_r_y], [0, 0, 0, -1]), 2)
+    hip_knee_l_angle = round(angle1([hip_l_x, hip_l_y, knee_l_x, knee_l_y], [0, 0, 0, -1]), 2)
+    neck_hip_angle = round(angle1([neck_x, neck_y, hip_r_x, hip_r_y], [0, 0, 0, -1]), 2)
+    # hip_knee_angle=round(angle1([hip_r_x, hip_r_y,knee_r_x, knee_r_y], [0, 0, 0, -1]), 2)
+    hip_heigh = hip_r_y
+
+    result["knee_ankle_r_angle"] = knee_ankle_r_angle
+    result["knee_ankle_l_angle"] = knee_ankle_l_angle
+    result["hip_knee_r_angle"] = hip_knee_r_angle
+    result["hip_knee_l_angle"] = hip_knee_l_angle
+    result["r_d"] = abs(float(result["hip_knee_r_angle"]) - float(result["knee_ankle_r_angle"]))
+
+    return result
+
+
+def ignore_data_jump(result_ig: dict):
+    max_index = max(result_ig.keys())
+    min_index = min(result_ig.keys())
+
+    max_leg_knee_angle = result_ig[min_index]["knee_ankle_angle"]
+    max_leg_knee_angle_num = int(min_index)
+    less_angle = 100
+    less_num = 1
+    ankle = result_ig[min_index]["leg_heigh"]
+    max_leg_knee_hip_knee = math.fabs(
+        float(result_ig[min_index]["hip_knee_angle"]) - float(result_ig[min_index]["knee_ankle_angle"]))
+    max_l_h_num = 1
+    hip_hei_init = float(result_ig[min_index]["hip_heigh"])
+    # print("max")
+    # print(max_index)
+    # print(hip_hei_init)
+
+    for i in result_ig:
+        if int(i) <= max_index / 5:
+            if float(max_leg_knee_angle) < float(result_ig[i]["knee_ankle_angle"]):
+                max_leg_knee_angle_num = int(i)
+                max_leg_knee_angle = result_ig[i]["knee_ankle_angle"]
+        if int(i) <= max_index / 2 and int(i) > max_index / 3:
+            val = math.fabs(
+                math.fabs(float(result_ig[i]["hip_knee_angle"])) - math.fabs(float(result_ig[i]["knee_ankle_angle"])))
+            if (math.fabs(math.fabs(float(result_ig[i]["hip_knee_angle"])) - math.fabs(
+                    float(result_ig[i]["knee_ankle_angle"]))) < less_angle):
+                less_angle = val
+                less_num = int(i)
+
+        if int(i) <= max_index and int(i) > (max_index / 3):
+
+            if (float(result_ig[i]["hip_heigh"])) < (float(hip_hei_init)) and max_l_h_num != 1:
+                break
+            if (math.fabs(math.fabs(float(result_ig[i]["hip_knee_angle"])) - math.fabs(
+                    float(result_ig[i]["knee_ankle_angle"])))) > max_leg_knee_hip_knee and math.fabs(
+                float(result_ig[i]["leg_heigh"]) - float(ankle)) <= 20:
+                max_leg_knee_hip_knee = math.fabs(
+                    float(result_ig[i]["hip_knee_angle"]) - math.fabs(float(result_ig[i]["knee_ankle_angle"])))
+                max_l_h_num = int(i)
+
+            #    ankle=result_ig[i]["leg_heigh"]
+            #    ankle_num=int(i)
+            # elif ankle!=1 and int(i)>=(le/3*2):
+            #    break
+
+    print(max_leg_knee_angle)
+    print(max_leg_knee_angle_num)
+    print(less_num)
+    print(less_angle)
+    # print(ankle)
+    # print(ankle_num)
+    print(max_leg_knee_hip_knee)
+    print(max_l_h_num)
+    re = {}
+    re["1"] = {}
+    re["1"]["num"] = max_leg_knee_angle_num
+    re["1"]["val"] = max_leg_knee_angle
+    re["2"] = {}
+    re["2"]["num"] = less_num
+    re["2"]["val"] = less_angle
+    re["3"] = {}
+    re["3"]["num"] = max_l_h_num
+    re["3"]["val"] = max_leg_knee_hip_knee
+    print(re)
+
+    return re
+
+
 class HighKneesVideoAnalyzer(BaseVideoAnalyzer):
     def __init__(self, video_uuid):
         super().__init__(video_uuid)
@@ -105,17 +392,15 @@ class CrunchVideoAnalyzer(BaseVideoAnalyzer):
 
 
 class StandingLongJumpVideoAnalyzer(BaseVideoAnalyzer):
-    def __init__(self, video_uuid):
-        super().__init__(video_uuid)
-
-    def analyze(self, callback: Callable):
-        try:
-            callback("RUNNING")
-
-            callback("FINISHED", result={})
-        except Exception as e:
-            callback("ERROR", error=e)
-            raise e
+    def _do_analyze(self):
+        frames_dir = UPLOAD_DIR + "frames/" + self.video_uuid + "/"
+        result = {}
+        for i in os.listdir(frames_dir):
+            if i.endswith(".npy"):
+                data = np.load(frames_dir + i)[0]
+                result_side = analyse_npy_side_jump(data)  # Analyze each frame
+                result[int(i.replace(".jpg.npy", ""))] = result_side  # Get the frame number to store the result
+        return ignore_data_jump(result)
 
 
 class PlankVideoAnalyzer(BaseVideoAnalyzer):