yolo | Implementation of the YOLO architecture using TensorFlow | Machine Learning library
kandi X-RAY | yolo Summary
kandi X-RAY | yolo Summary
Implementation of YOLO in Tensorflow. Currently debugging cost function.
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Top functions reviewed by kandi - BETA
- Visualize and save images
- Load images and labels and labels
- Clean image and pickle
- Load the reel image
- Split images into train and test sets
- Convert pixel coordinates to grid coordinates
- Builds the layers from the input image
- Get the output shape
- Train the network
- Get batches of images in the image
- Test yolo
- Sets a session
- Forward computation
- Normalization function
- Check the input data
- Evaluate the test
- Run yolo with debug mode
- Generate a latex equation for the equation
- Run yolo network
- Cleans up raw images from yolo
yolo Key Features
yolo Examples and Code Snippets
Community Discussions
Trending Discussions on yolo
QUESTION
I want to detect more objects than coco dataset which detects only 80 objects , I want to detect as many as possible actions also like hugging ,swimming.....etc.
I don't care about the size and I do not want to train myself ... So is there a dataset(weights) big enough already available that I can download and use or I do have to train and label for yolo?
...ANSWER
Answered 2021-Jun-13 at 13:54What you are trying to classify is represented as Action Recognition. Here [1] is a good repo that lists a lot of out-of-the-box models for this task.
An explanation: Models (like YOLO) contain two main blocks: feature extraction (CNN stuff) and classification (linear layers). When training from scratch, both feature extraction and classification will be trained from scratch. It is easy to train classification to what you want, but it is hard to train the feature extraction part (as it takes a lot of time). Hence, we typically use pre-trained models on generalized datasets (like YOLO is trained on COCO), so our feature extraction part starts from a somewhat good generalized place. Later, we replace the classification part will our own to be trained from scratch for our task.
TL;DR, you can use a pre-trained YOLO model on COCO for your task by replacing the last linear layers to classify what you want. Here are some resources for different frameworks [2, 3].
Here [4] is a simple walkthrough of how to do this.
- [1] https://github.com/jinwchoi/awesome-action-recognition/blob/master/README.md#action-recognition-and-video-understanding
- [2] TensorFlow: https://www.tensorflow.org/tutorials/images/transfer_learning
- [3] PyTorch: https://pytorch.org/tutorials/beginner/transfer_learning_tutorial.html
- [4] https://blog.roboflow.com/training-yolov4-on-a-custom-dataset/
QUESTION
I'm trying to populate a table from an array of objects. The html is a simple table that get's populated from the following piece of code.
The image that corresponds to each row has the same URL and is in the same folder ,however it has a different id (I simply call them 1.png, 2.png 3.png.... and so on ).
Basically, I'm trying to construct each URL by concatenating the id. to the same URL over and over for each new row.
All works well except the video part where the URL construction fails. Am I missing something here while concatenating the URL?
...ANSWER
Answered 2021-Jun-09 at 12:56The line containing the img should be:
QUESTION
I have installed a couple of dependencies in editable state using pip install -e path/to/project, using the command parameter -e for the first time today.
For the first dependency, the project sort, everything worked perfectly.
But for the other dependency, the project yolov3 things didn't work out as fine, although I have used the same exact commands:
To installation
...ANSWER
Answered 2021-Jun-07 at 10:29For a precise answer, you would have to provide the project structure of the package yolov3. But I guess the problem is that the package yolov3, does not include a module to build.
A minimal project structure has to look like this:
QUESTION
As I try to covert my yolov4-tiny custom weight to tftile, it always happen.
This is what I input:
...ANSWER
Answered 2021-Jun-06 at 14:03You have to add --tiny to the command. Which, from the command you gave in the question, will be.
QUESTION
I have a data.frame with a column containing California counties in each cell separated by a space. I would like to add a comma and space after each one, however I can't just gsub every space into a comma and space, (i.e. gsub("\s",",\s",text)), as some counties in California have two names, (e.g. Los Angeles, San Francisco, etc.)
Fortunately, the two-word counties all have common first words so I'd like to write a gsub that preserves the space in those counties without adding a comma. I've attached example data as well as what I'd like the final form to look like. For instance, with this data, I'd like to add a comma and space except after "El", "San" and "Del".
Example data:
...ANSWER
Answered 2021-Jun-05 at 00:29Given that you know you are only looking for California counties, one "easy" way is just to replace only spaces that occur after a California county. To get that regex, I just concatenated the CA county names together with | and added a space. The gsub will replace any county name followed by a space with the same county name (\\1), a comma, and a space.
QUESTION
I was trying to train a dataset in yolov4 but I had some errors coming up while training about my annotations being in the wrong format.
The dataset had its annotations in a CSV with the format
...ANSWER
Answered 2021-Jun-03 at 06:36I think you messed up calculating x and y:
YOLO usses x_min position and y_min position (normalised, <1), which is the top left corner of your bounding box. Plus the distance of the box along the x axes (w) and the y axes (h).
I think that with x being the mean at our code
(xcen = ((df.x_min + df.x_max)) / 2 / df['width'])
xcen+w can be higher than one and might give errors
and that what happens exactly in your first line of data
QUESTION
This program is detecting the things from web cam but it's slow so how can i make it fast for better FPS and how can i use GPU for the faster detection and with better performance. And i how can i make it perfect .In this Program i have used the Yolo configuration and weights with coco dataset .
...ANSWER
Answered 2021-May-31 at 11:45To use Gpu we have to compile opencv and this can be done as follows in blog : https://haroonshakeel.medium.com/build-opencv-4-4-0-with-cuda-gpu-support-on-windows-10-without-tears-aa85d470bcd0
and after doing it add the two lines that will that will detect the Gpu and program will run on GPU.
QUESTION
I want to deploy a pytorch model with aws sam. my folder structure looks as follows:
...ANSWER
Answered 2021-May-29 at 02:37Thing you are missing is if you trying load folder as package you have to create proper packaging in Python. Else you can get all files one by one imported in your app.py
Steps to create package :
- Create folder name
models - Create
__init__.pyfile insidemodelsfolder - create your other files like
yolo.py,experimental.py,common.pyetc - Then load all four into
__init__.pyfile like below
QUESTION
I am running a tensorflow model on google colab. Today, I got this error:
...ANSWER
Answered 2021-May-27 at 03:19Try downgrading Python to 3.6 using this link. You need to re-install the packages you previously used.
QUESTION
I'm looking for something that can help me with detection of eye via YOLO method. Is it even possible? Saw that COCO and pascal VOC datasets are wide but there's lack of eye class. Is there any dataset or something that could help me with such detection?
...ANSWER
Answered 2021-May-24 at 15:51You can manually train for custom classes. If you have GPU you can use or else use Google Colab. Here is the link for tutorial
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
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Install yolo
You can use yolo like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.
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