Question

我在opencv中遇到numpy问题。

我是opencv的新手，我正在尝试在视频对象跟踪器中找到矩形的中心，但是会引发以下错误：

Traceback (most recent call last):
  File "track_p_copia.py", line 45, in <module>
    objects = ct.update(rects)
  File "D:\git_up\job_room\center\center_id.py", line 36, in update
    for i in range(0, inputCentroids):
TypeError: only integer scalar arrays can be converted to a scalar index

跟踪视频中人物并创建矩形的代码如下：

import cv2 
import numpy as np 
from center.center_id import CentroidTracker


ct = CentroidTracker()


cap = cv2.VideoCapture(r'C:\Users\Usuario\Downloads\camina2.mp4') #change please

ret, frame1 = cap.read()
ret, frame2 = cap.read()
rects = []

while cap.isOpened():
    
        diff = cv2.absdiff(frame1, frame2)
        gray = cv2.cvtColor(diff, cv2.COLOR_BGR2GRAY)
        blur = cv2.GaussianBlur(gray, (5,5),0)
        _, thresh = cv2.threshold(blur, 20, 255, cv2.THRESH_BINARY)
        dilated = cv2.dilate(thresh, None, iterations=3)
        contours, _ = cv2.findContours(dilated, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
            
        for c in contours:
            (x, y, w, h) = cv2.boundingRect(c)
            if cv2.contourArea(c) < 700:
                continue
            rectangle = [x, y, (x + w), (y + h)] 
            rects.append(rectangle)
            cv2.rectangle(frame1, (rectangle[0], rectangle[1]), (rectangle[2], rectangle[3]),(0, 255, 0), 2)       
        
        #Detect centroIDs
        objects = ct.update(rects)
        if objects is not None:
            for (objectID, centroid) in objects.items():
                text = "ID:{}".format(objectID)
                cv2.putText(frame, text, (centroid[0] - 10, centroid[1] - 10),
                             cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 255, 0), 2)
                cv2.circle(frame, (centroid[0], centroid[1]), 4, (0, 255, 0), -1)
        
        cv2.imshow("feed", frame1)
        frame1 = frame2
        ret, frame2= cap.read()

        if cv2.waitKey(40) == 32 or cv2.waitKey(40) == 27:          
            break

cv2.destroyAllWindows()
cap.release()

我从教程中获取的用于找到矩形的中心ID并更新ID中心位置的代码如下：

from scipy.spatial import distance as dist
from collections import OrderedDict
import numpy as np

#Makes a the next unique object ID with
#2 ordered dictionaries
class CentroidTracker():
    def __init__(self, maxDisappeared = 50):
        self.nextObjectID = 0
        self.objects = OrderedDict()
        self.disappeared = OrderedDict()
        self.maxDisappeared = maxDisappeared

    def register(self, centroid):
        self.objects[self.nextObjectID] = centroid
        self.disappeared[self.nextObjectID] = 0
        self.nextObjectID += 1

    def deregister(self, objectID):
        del self.objects[objectID]
        del self.disappeared[objectID]

    def update(self, rects):
        if len(rects) == 0:
            for objectID in self.disappeared.keys():
                self.disappeared[objectID] += 1
                if self.disappeared[objectID] > self.maxDisappeared:
                    self.deregister(objectID)
            return self.objects
        inputCentroids = np.zeros((len(rects), 2), dtype="int")
        for (i, (startX, startY, endX, endY)) in enumerate(rects):
            cX = int((startX + endX) / 2.0)
            cY = int((startY + endY) / 2.0)
            inputCentroids[i] = (cX, cY)
        if len(self.objects) == 0:
            for i in range(0, inputCentroids):
                self.register(inputCentroids[i])
        else:
            objectIDs = list(self.objects.keys())
            objectCentroids = list(self.objects.values())
            D = dist.cdist(np.array(objectCentroids), inputCentroids)
            rows = D.min(axis=1).argsort()
            cols = D.argmin(axis=1)[rows]

            usedRows = set()
            usedCols = set()

            for (row, col) in zip(rows, cols):
                if row in usedRows or col in usedCols:
                    continue
                objectID = objectIDs[row]
                self.objects[objectID] = inputCentroids[col]
                self.disappeared[objectID] = 0
                usedRows.add(row)
                usedCols.add(col)
                # compute both the row and column index we have NOT yet
                # examined
                unusedRows = set(range(0, D.shape[0])).difference(usedRows)
                unusedCols = set(range(0, D.shape[1])).difference(usedCols)
                if D.shape[0] >= D.shape[1]:
                    # loop over the unused row indexes
                    for row in unusedRows:
                        # grab the object ID for the corresponding row
                        # index and increment the disappeared counter
                        objectID = objectIDs[row]
                        self.disappeared[objectID] += 1

                        # check to see if the number of consecutive
                        # frames the object has been marked "disappeared"
                        # for warrants deregistering the object
                        if self.disappeared[objectID] > self.maxDisappeared:
                            self.deregister(objectID)
                else:
                    for col in unusedCols:
                        self.register(inputCentroids[col])

                    # return the set of trackable objects
                return self.objects

我知道错误必须出在创建矩形的代码中，而不是在ID中心的搜索引擎中，因为我是从专家教程中获得的。有人可以帮我知道我哪里错了吗？。我知道该错误与Numpy有关，但我很困惑

Answer 1

这不是opencv问题。这是对pd.concat([animals_data, numbers_data], keys=['animal','number'], axis=1)的简单滥用，它仅接受数字，不接受数组或列表等：

  animal         number   
       A       B      A  B
0    Dog   Horse      1  3
1    Cat  Donkey      2  4

为什么在opencv中使用numpy时会抛出错误？

1 个答案: