How To Train an Object Detection Neural Network Using TensorFlow (GPU) on Windows 10
Why Stack Overflow recommends it
Stack Overflow users link it as the tutorial they followed for TensorFlow object detection, usually when asking for help with errors that appear at specific steps, and sometimes as a recommended end-to-end walkthrough.
Recommended by 1 people across 1 different months, 2018 to 2021.
What it is
A 30-minute step-by-step tutorial by Edje Electronics on training a custom multi-object detector with Google's TensorFlow Object Detection API on Windows 10 using an Nvidia GPU. It covers installing TensorFlow-GPU, setting up an Anaconda environment, labeling images with LabelImg, generating TFRecords, configuring and running training, and exporting an inference graph.
What people said
Recommends Aashay Sharma · 2020-04 · Stack Overflow · on “Locate Handwritten Notes within Text-Based Image”
you can label images with this kind of data using googles object detection API using tensor flow, try and use faster rcnn model for accuracy, construct your training data using these kind of images(shown in your query) and labelling the part that you want to detect , after training data is done use that data to make detections and based on that detection you will get bounding boxes for which you can get co-ordinates very easily if you are working with googles tensor flow object detection API check this link for more detailed and complete process : [this video]
Cites Tanzeel Ahmed · 2018-04 · Stack Overflow · on “Training different objects using tensorflow Object detection API”
I recently came across this link for learning tensorflow object detection [this video] However I have few doubts and want suggestion on how to proceed. 1) How should I train different objects using the same model( I mean what should my data set contain if I want to train cats,dogs as objects. 2) and once I have trained it for dogs and then continue training on cars will the model detect dogs?
Cites 9hyo · 2018-07 · Stack Overflow · on “ImportError: cannot import name 'abs'”
I got problem while doing object detection using tensorflow-gpu I was follwing the youtube tutorials : [this video] I'm trying to detect object using tensorflow-gpu with virtual environment. I added python, cuda, tensorflow to system environment variables, and also did make training models with labels. I converted xml labels to csv using xml_to_csv.py. The problem is when I try to generate tfrecord using generate_tfrecord.py, that error appear. Please help Here's the code (tensorflow) C:\Users\ice305\tensorflow\models\research\object_detection>python generate_tfrecord.py --csv_input=images\train_labels.csv --image_dir=images\train --output_path=train.record Traceback (most recent call last): File
Cites Dawood Zaidi · 2018-09 · Stack Overflow · on “Python - Entry Point Not Found”
Was following an Object Detection tutorial: [this video] Set up Tensorflow-gpu 1.9.0 Cuda 9.0 Cudnn 7 When I run the train.py I recieve an error that says: [LINK] When I used Tensorflow-gpu version 1.5.0 (Just like in the video) I got an error that Said: " non_max_suppression() got an unexpected keyword argument 'score_threshold' " Upon research I got to know that i have to use Tensorflow 1.9 or above to avoid this error. I've tried implementing everything in order for like 3 times now and this error remains.
Cites Zoltan Torok · 2019-12 · Stack Overflow · on “Tensorflow TypeError: expected bytes, Descriptor found”
I've been following this tutorial for recognising an object using machine learning: [this video] I've followed all the instructions on what to install and how, including those in this related tutorial: [LINK] I tried both with their version and the newest available versions of the software. With the exception that I create the virtual environment like this: conda create -n tensorflow1 pip python=3.6 Because the tensorflow module isn't yet compatible with python 3.7. After I install all the packages needed, also described here: [LINK] Under 2d. Set up new Anaconda virtual environment and go through the code in the video, I run into a error when I run python generate_tfrecord.py --csv_input=images\
Cites GilBenDavid · 2020-02 · Stack Overflow · on “Tensorflow should I separate object sides?”
I'm working on a project that uses tensorflow to detect a specific object. That object can be laying on a table or any other surface and it has two sides, both of the sides look different from each other. I'm following this tutorial to build my object detection model: Object detection with tensorflow tutorial [this video] Currently I'm on the labeling step and I need to know if I should separate the back and the front of the object to two different labels (I don't need to separate it for my code, I just need to know if it is the object I'm searching for) and what is the right way to do that with google object detection api.
Cites PedroJung · 2021-07 · Stack Overflow · on “tensorflow object detection...python model_main_tf2.py --model_di .... command cause error utf-8”
I command as below (tensorflow1) C:\tensorflow1\models\research\object_detection>python model_main_tf2.py --model_dir=ssd_mobilenet_v2_fpnlite_320x320_coco17_tpu-8 --pipeline_config_path=ssd_mobilenet_v2_fpnlite_320x320_coco17_tpu-8/pipline.config --num_train_steps=10000 and it causes error The versions of TensorFlow you are currently using is 2.6.0-rc1 and is not supported. Some things might work, some things might not. If you were to encounter a bug, do not file an issue. If you want to make sure you're using a tested and supported configuration, either change the TensorFlow version or the TensorFlow Addons's version. You can find the compatibility matrix in TensorFlow Addon's readme: [LIN