python - 使用网络摄像头执行 opencv / maskrcnn 时，我收到“NoneType”错误的原因是因为我的笔记本电脑上没有 GPU？

Question

运行下面的代码 - 尝试使用 opencv 和我的网络摄像头实现 maskrcnn。

当我设置PROCESS_IMG = False时，输出很好，显示网络摄像头输入以及 FPS（如果我将其设置为 false）。

我试图注释掉该行s = masked_image和下面的行，每 4-5 秒我会刷新一次网络摄像头以及覆盖在顶部的适当 maskrcnn 输出（这就是我想要的）。

不假设我会以任何方式获得 60fps，0.2fps 就可以了。

import os
import sys
import cv2
import time
import imutils
import numpy as np
import mrcnn.model as modellib
from mrcnn import utils, visualize
from imutils.video import WebcamVideoStream
import random

# Root directory of the project
from samples.coco.coco import CocoConfig

ROOT_DIR = os.path.abspath("./")

sys.path.append(os.path.join(ROOT_DIR, "samples/coco/"))  # To find local version

# Directory to save logs and trained model
MODEL_DIR = os.path.join(ROOT_DIR, "logs")

# Local path to trained weights file
COCO_MODEL_PATH = os.path.join(ROOT_DIR, "mask_rcnn_coco.h5")
# Download COCO trained weights from Releases if needed
if not os.path.exists(COCO_MODEL_PATH):
    utils.download_trained_weights(COCO_MODEL_PATH)

class InferenceConfig(CocoConfig):
    # Set batch size to 1 since we'll be running inference on
    # one image at a time. Batch size = GPU_COUNT * IMAGES_PER_GPU
    GPU_COUNT = 1
    IMAGES_PER_GPU = 1

config = InferenceConfig()
config.display()

# Create model object in inference mode.
model = modellib.MaskRCNN(mode="inference", model_dir=MODEL_DIR, config=config)

# Load weights trained on MS-COCO
model.load_weights(COCO_MODEL_PATH, by_name=True)

# COCO Class names
# Index of the class in the list is its ID. For example, to get ID of
# the teddy bear class, use: class_names.index('teddy bear')
class_names = ['BG', 'person', 'bicycle', 'car', 'motorcycle', 'airplane',
               'bus', 'train', 'truck', 'boat', 'traffic light',
               'fire hydrant', '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']

colors = visualize.random_colors(len(class_names))

gentle_grey = (45, 65, 79)
white = (255, 255, 255)

OPTIMIZE_CAM = True
SHOW_FPS = False
SHOW_FPS_WO_COUNTER = False  # faster
PROCESS_IMG = True


if OPTIMIZE_CAM:
    vs = WebcamVideoStream(src=0).start()
else:
    vs = cv2.VideoCapture(0)

if SHOW_FPS:
    fps_caption = "FPS: 0"
    fps_counter = 0
    start_time = time.time()

SCREEN_NAME = 'Mask RCNN LIVE'
cv2.namedWindow(SCREEN_NAME, cv2.WINDOW_NORMAL)
cv2.setWindowProperty(SCREEN_NAME, cv2.WND_PROP_FULLSCREEN, cv2.WINDOW_FULLSCREEN)

while True:
    # Capture frame-by-frame
    if OPTIMIZE_CAM:
        frame = vs.read()
    else:
        grabbed, frame = vs.read()
        if not grabbed:
            break
    
    if SHOW_FPS_WO_COUNTER:
        start_time = time.time() # start time of the loop

    if PROCESS_IMG:    
        results = model.detect([frame])
        r = results[0]

        # Run detection
        masked_image = visualize.display_instances(frame, r['rois'], r['masks'], 
            r['class_ids'], class_names, r['scores'], colors=colors)
        
    if PROCESS_IMG:
        s = masked_image
    else:
        s = frame
    print("Image shape: {1}x{0}".format(s.shape[0], s.shape[1]))

    width = s.shape[1]
    height = s.shape[0]
    top_left_corner = (width-120, height-20)
    bott_right_corner = (width, height)
    top_left_corner_cvtext = (width-80, height-5)

    if SHOW_FPS:
        fps_counter+=1
        if (time.time() - start_time) > 5 : # every 5 second
            fps_caption = "FPS: {:.0f}".format(fps_counter / (time.time() - start_time))
            # print(fps_caption)
            fps_counter = 0
            start_time = time.time()
        ret, baseline = cv2.getTextSize(fps_caption, cv2.FONT_HERSHEY_SIMPLEX, 0.5, 1)
        cv2.rectangle(s, (width - ret[0], height - ret[1] - baseline), bott_right_corner, gentle_grey, -1)
        cv2.putText(s,fps_caption, (width - ret[0], height - baseline), cv2.FONT_HERSHEY_SIMPLEX, 0.5, white, lineType=cv2.LINE_AA)

    if SHOW_FPS_WO_COUNTER:
        # Display the resulting frame
        fps_caption = "FPS: {:.0f}".format(1.0 / (time.time() - start_time))
        # print("FPS: ", 1.0 / (time.time() - start_time))
        
        # Put the rectangle and text on the bottom left corner
        ret, baseline = cv2.getTextSize(fps_caption, cv2.FONT_HERSHEY_SIMPLEX, 0.5, 1)
        cv2.rectangle(s, (width - ret[0], height - ret[1] - baseline), bott_right_corner, gentle_grey, -1)
        cv2.putText(s, fps_caption, (width - ret[0], height - baseline),
                    cv2.FONT_HERSHEY_SIMPLEX, 0.5, white, 1, lineType=cv2.LINE_AA)

    
    s = cv2.resize(s,(1920,1080))
    cv2.imshow(SCREEN_NAME, s)
    cv2.waitKey(1)
    if cv2.waitKey(1) & 0xFF == ord('q'): break
    
# When everything done, release the capture
if OPTIMIZE_CAM:
    vs.stop()
else:
    vs.release()
cv2.destroyAllWindows()

错误：

AttributeError                            Traceback (most recent call last)
<ipython-input-1-d3debbeb3ebd> in <module>
    109     else:
    110         s = frame
--> 111     print("Image shape: {1}x{0}".format(s.shape[0], s.shape[1]))
    112 
    113     width = s.shape[1]

AttributeError: 'NoneType' object has no attribute 'shape'

如果我添加这个代码，我会得到一个带有正确掩码的图像：

file_names = next(os.walk(IMAGE_DIR))[2]
image = skimage.io.imread(os.path.join(IMAGE_DIR, random.choice(file_names)))

start = time.time()
# Run detection
results = model.detect([image], verbose=1)
end = time.time()
print("Time:",end-start,"seconds")

# Visualize results
r = results[0]
visualize.display_instances(image, r['rois'], r['masks'], r['class_ids'], 
                            class_names, r['scores'])

标签： pythontensorflowopencvconv-neural-network

Answer 1

visualize.display_instances()不返回任何东西，所以在 python 中它None默认返回。所以你设置masked_image在None这条线上：

masked_image = visualize.display_instances(...

然后你设置s到None这一行：

s = masked_image

所以 thens.shape不能工作并抛出你得到的错误。