如何使用 FasterRCNN Openimages v4？

Question

我似乎找不到任何关于如何使用此模型的文档。我正在尝试用它打印出视频中出现的对象任何帮助将不胜感激我才刚开始所以对我放轻松

Answer 1

I am trying to use it to print out the objects that appear in a video

我理解你的问题是打印出找到的对象的名称。

我不知道你是如何实现在 OpenImages v4 上训练 Fast RCNN 的地方的。因此，我会给你the model from Tensorflow Hub. Google Colab. AI Hub

的方法

Answer 2

经过一番挖掘和大量试验和错误后，我想到了这个

#!/home/ahmed/anaconda3/envs/TensorFlow/bin/python3.8
import tensorflow as tf
import tensorflow_hub as hub
import time,imageio,sys,pickle

# sys.argv[1] is used for taking the video path from the terminal
video = sys.argv[1]
#passing the video file to ImageIO to be read later in form of frames
video = imageio.get_reader(video)
dictionary = {}
#download and extract the model( faster_rcnn/openimages_v4/inception_resnet_v2 or
# openimages_v4/ssd/mobilenet_v2) in the same folder
module_handle = "*Path to the model folder*"
detector = hub.load(module_handle).signatures['default']
#looping over every frame in the video
for index, frames in enumerate(video):
    # converting the images ( video frames ) to tf.float32 which is the only acceptable input format
    image = tf.image.convert_image_dtype(frames, tf.float32)[tf.newaxis]
    # passing the converted image to the model
    detector_output = detector(image)
    class_names = detector_output["detection_class_entities"]
    scores = detector_output["detection_scores"]
    # in case there are multiple objects in the frame
    for i in range(len(scores)):
        if scores[i] > 0.3:
            #converting form bytes to string
            object = class_names[i].numpy().decode("ascii")
            #adding the objects that appear in the frames in a dictionary and their frame numbers
            if object not in dictionary:
                dictionary[object] = [index]
            else:
                dictionary[object].append(index)
print(dictionary)

如何使用 FasterRCNN Openimages v4？

How to use FasterRCNN Openimages v4?

tensorflow

keras

tensorflow2.0

object-detection

faster-rcnn