RuntimeError：对象没有属性nms：

如何解决RuntimeError：对象没有属性nms：

所以我正在按照本教程构建对象检测，但遇到一个错误，我的朋友都没有得到（请注意，代码正在MacOS中运行）。我附上了错误消息

的屏幕截图，如果遇到任何帮助，我会不断得到它。

import torchvision
import cv2
import matplotlib.pyplot as plt
from PIL import Image
from torchvision import transforms as T

model = torchvision.models.detection.fasterrcnn_resnet50_fpn(pretrained=True)
model.eval()

COCO_INSTANCE_CATEGORY_NAMES = [
    '__background__','person','bicycle','car','motorcycle','airplane','bus','train','truck','boat','traffic light','fire hydrant','N/A','stop sign','parking meter','bench','bird','cat','dog','horse','sheep','cow','elephant','bear','zebra','giraffe','backpack','umbrella','handbag','tie','suitcase','frisbee','skis','snowboard','sports ball','kite','baseball bat','baseball glove','skateboard','surfboard','tennis racket','bottle','wine glass','cup','fork','knife','spoon','bowl','banana','apple','sandwich','orange','broccoli','carrot','hot dog','pizza','donut','cake','chair','couch','potted plant','bed','dining table','toilet','tv','laptop','mouse','remote','keyboard','cell phone','microwave','oven','toaster','sink','refrigerator','book','clock','vase','scissors','teddy bear','hair drier','toothbrush'
]


def get_prediction(img_path,threshold):
    img = Image.open(img_path)  # Load the image
    transform = T.Compose([T.ToTensor()])  # Defing PyTorch Transform
    img = transform(img)  # Apply the transform to the image
    pred = model([img])  # Pass the image to the model
    pred_class = [COCO_INSTANCE_CATEGORY_NAMES[i] for i in list(pred[0]['labels'].numpy())]  # Get the Prediction Score
    pred_boxes = [[(i[0],i[1]),(i[2],i[3])] for i in list(pred[0]['boxes'].detach().numpy())]  # Bounding boxes
    pred_score = list(pred[0]['scores'].detach().numpy())
    pred_t = [pred_score.index(x) for x in pred_score if x > threshold][
        -1]  # Get list of index with score greater than threshold.
    pred_boxes = pred_boxes[:pred_t + 1]
    pred_class = pred_class[:pred_t + 1]
    return pred_boxes,pred_class


def object_detection_api(img_path,threshold=0.5,rect_th=3,text_size=3,text_th=3):
    boxes,pred_cls = get_prediction(img_path,threshold)  # Get predictions
    img = cv2.imread(img_path)  # Read image with cv2
    img = cv2.cvtColor(img,cv2.COLOR_BGR2RGB)  # Convert to RGB
    for i in range(len(boxes)):
        cv2.rectangle(img,boxes[i][0],boxes[i][1],color=(0,255,0),thickness=rect_th)  # Draw Rectangle with the coordinates
        cv2.putText(img,pred_cls[i],cv2.FONT_HERSHEY_SIMPLEX,text_size,(0,thickness=text_th)  # Write the prediction class
    plt.figure(figsize=(20,30))  # display the output image
    plt.imshow(img)
    plt.xticks([])
    plt.yticks([])
    plt.show()


object_detection_api('./people.jpg',threshold=0.8)

解决方法

我不知道为什么它不起作用，但是在更新了我的python版本之后，它终于起作用了（3.7.6-> 3.8.5）。