object-detection-api

问题 I am training tensorflow object detection API model on the custom dataset i.e. License plate dataset. My goal is to deploy this model to the edge device using tensorflow lite so I can't use any RCNN family model . Because, I can't convert any RCNN family object detection model to tensorflow lite model (this is the limitation from tensorflow object detection API). I am using ssd_mobilenet_v2_coco model to train the custom dataset. Following is the code snippet of my config file: model { ssd {

问题 How to find predicted image id and Box from SSD, I am using this GitHub link here is the test function which I want to save the image id and box def test(loader, net, criterion, device): net.eval() running_loss = 0.0 running_regression_loss = 0.0 running_classification_loss = 0.0 num = 0 for _, data in enumerate(loader): images, boxes, labels = data images = images.to(device) boxes = boxes.to(device) labels = labels.to(device) num += 1 with torch.no_grad(): confidence, locations = net(images)

问题 I ask the question because I wanted to solve the error I experienced. I want to use 'SSD lite Mobilenet V2' in Raspberry Pi 3 B+ and NCS(not 2, it is NCS1). So I installed OpenVINO 2019_R3 on my Pi(Raspbian stretch) and Laptop(Linux, not all programs, just Model optimizer). When I optimize SSD lite mobilenet v2(trained zoo model), it was fine. So, i trained my model in Google Colab using Tensorflow object detection api. But when I optimize my own SSD lite model, here is log and what I typed

问题 I ask the question because I wanted to solve the error I experienced. I want to use 'SSD lite Mobilenet V2' in Raspberry Pi 3 B+ and NCS(not 2, it is NCS1). So I installed OpenVINO 2019_R3 on my Pi(Raspbian stretch) and Laptop(Linux, not all programs, just Model optimizer). When I optimize SSD lite mobilenet v2(trained zoo model), it was fine. So, i trained my model in Google Colab using Tensorflow object detection api. But when I optimize my own SSD lite model, here is log and what I typed

问题 I have trained an SSD Mobilenet model with custom dataset(Battery). Sample image of the battery is given below and also attached the config file which I used to train the model. When the object is closer to the camera(tested with webcam) it detects the object accurately with probability over 0.95 but when I move the object to a longer distance it is not getting detected. Upon debugging, Found that the object gets detected but with the lower probability 0.35 . The minimum threshold is set to 0

问题 I have trained tensorflow object detection model (for num_steps:50000 ) using SSD (mobilenet-v1) on custom dataset. I got mAP@.50IOU ~0.98 and loss ~1.17. The dataset consist of uno playing card images (skip, reverse, and draw four). On all these cards, model performs pretty well as I have trained model only on these 3 card (around 278 images with 829 bounding boxes (25% bounding box used for testing i.e. validation) collected using mobile phone). However, I haven’t trained model on any other

问题 I started using the cocoapi to evaluate a model trained using the Object Detection API. After reading various sources that explain mean average precision (mAP) and recall, I am confused with the "maximum detections" paramter used in the cocoapi. From what I understood (e.g. here, here or here), one calculates mAP by calculating precision and recall for various model score thresholds. This gives the precision-recall curve and mAP is calculated as an approximation to the area under this curve.

问题 I have a mac and I am using tensorflow 2.0, python 3.7. I am following the tutorial for creating an object detection model for real-time application. but i am getting the following error: "Downloads/models/research/object_detection/object_detection_tutorial.py", line 43, in od_graph_def = tf od_graph_def = tf.GraphDef() AttributeError: module 'tensorflow' has no attribute 'GraphDef' below is the tutorial link: I checked the environment and I already have tensorflow environment in anaconda

问题 I have a mac and I am using tensorflow 2.0, python 3.7. I am following the tutorial for creating an object detection model for real-time application. but i am getting the following error: "Downloads/models/research/object_detection/object_detection_tutorial.py", line 43, in od_graph_def = tf od_graph_def = tf.GraphDef() AttributeError: module 'tensorflow' has no attribute 'GraphDef' below is the tutorial link: I checked the environment and I already have tensorflow environment in anaconda

问题 I am super new to the field of object detection. I was wondering if anyone can help me somehow on how I can download and use the object detection datasets such as coco or pascal. When I go to their website even after downloading the datasets i feel like i dont know what should i do with them... I know this question is stupid, but a hint to start can be super useful. Thanks 回答1: I'm using: python 3.5 on Ubuntu 16.04 Firstly, there are three things you'd want to download and unzip: 1) Cocoapi -