tensorrt-yolov4 | Full pipeline from model training | MLOps library

 by   tmralmeida Python Version: Current License: Apache-2.0

kandi X-RAY | tensorrt-yolov4 Summary

kandi X-RAY | tensorrt-yolov4 Summary

tensorrt-yolov4 is a Python library typically used in Data Preparation, MLOps, Deep Learning, Pytorch, Tensorflow applications. tensorrt-yolov4 has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. However tensorrt-yolov4 build file is not available. You can download it from GitHub.

Full pipeline from model training to deployment on Nvidia AGX Xavier
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            kandi-support Support

              tensorrt-yolov4 has a low active ecosystem.
              It has 5 star(s) with 0 fork(s). There are 2 watchers for this library.
              OutlinedDot
              It had no major release in the last 6 months.
              tensorrt-yolov4 has no issues reported. There are no pull requests.
              It has a neutral sentiment in the developer community.
              The latest version of tensorrt-yolov4 is current.

            kandi-Quality Quality

              tensorrt-yolov4 has 0 bugs and 0 code smells.

            kandi-Security Security

              tensorrt-yolov4 has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
              tensorrt-yolov4 code analysis shows 0 unresolved vulnerabilities.
              There are 0 security hotspots that need review.

            kandi-License License

              tensorrt-yolov4 is licensed under the Apache-2.0 License. This license is Permissive.
              Permissive licenses have the least restrictions, and you can use them in most projects.

            kandi-Reuse Reuse

              tensorrt-yolov4 releases are not available. You will need to build from source code and install.
              tensorrt-yolov4 has no build file. You will be need to create the build yourself to build the component from source.
              Installation instructions are not available. Examples and code snippets are available.
              It has 1331 lines of code, 74 functions and 9 files.
              It has high code complexity. Code complexity directly impacts maintainability of the code.

            Top functions reviewed by kandi - BETA

            kandi has reviewed tensorrt-yolov4 and discovered the below as its top functions. This is intended to give you an instant insight into tensorrt-yolov4 implemented functionality, and help decide if they suit your requirements.
            • Build onnx graph
            • Create onnx node
            • Loads conv layer weights
            • Create the input tensor
            • Create convolution layer
            • Return the previous node that was created onnx
            • Generate a param name
            • Opens the camera
            • Open camera on screen
            • Create a cv2 video capture
            • Load GPU engine
            • Open a window
            • Start the background thread
            • Return the class dict for a given category number
            • Generate md5 checksum for local file
            • Grab an image from the pool
            • Opens the weights file
            • Parse a config file
            • Parse command line arguments
            • Creates a shortcut node
            • Creates a max pool node
            • Loop through a video and detect box detection
            • Create an upsample node
            • Build an engine
            • Create route node
            • Stops the thread
            Get all kandi verified functions for this library.

            tensorrt-yolov4 Key Features

            No Key Features are available at this moment for tensorrt-yolov4.

            tensorrt-yolov4 Examples and Code Snippets

            No Code Snippets are available at this moment for tensorrt-yolov4.

            Community Discussions

            QUESTION

            Prepare for Binary Masks used for the image segmentation
            Asked 2022-Mar-30 at 08:33

            I am trying to prepare the masks for image segmentation with Pytorch. I have three questions about data preparation.

            1. What is the appropriate data format to save the binary mask in general? PNG? JPEG?

            2. Is the mask size needed to be set square such as (224x224), not a rectangle such as (224x448)?

            3. Is the mask value fixed when the size is converted from rectangle to square?

            For example, the original mask image size is (600x900), which is binary [0,1]. However, when I applied

            ...

            ANSWER

            Answered 2022-Mar-30 at 08:33
            1. PNG, because it is lossless by design.
            2. It depends. More convenient is to use standard resolution, (224x224), I would start with that.
            3. Use resize without interpolation transforms.Resize((300, 300), interpolation=InterpolationMode.NEAREST)

            Source https://stackoverflow.com/questions/71669952

            QUESTION

            Yolov5 object detection training
            Asked 2022-Mar-25 at 04:06

            Please i need you help concerning my yolov5 training process for object detection!

            I try to train my object detection model yolov5 for detecting small object ( scratch). For labelling my images i used roboflow, where i applied some data augmentation and some pre-processing that roboflow offers as a services. when i finish the pre-processing step and the data augmentation roboflow gives the choice for different output format, in my case it is yolov5 pytorch, and roboflow does everything for me splitting the data into training validation and test. Hence, Everything was set up as it should be for my data preparation and i got at the end the folder with data.yaml and the images with its labels, in data.yaml i put the path of my training and validation sets as i saw in the GitHub tutorial for yolov5. I followed the steps very carefully tought.

            The problem is when the training start i get nan in the obj and box column as you can see in the picture bellow, that i don't know the reason why, can someone relate to that or give me any clue to find the solution please, it's my first project in computer vision.

            This is what i get when the training process starts

            This the last message error when the training finish

            I think the problem comes maybe from here but i don't know how to fix it, i used the code of yolov5 team as it's in the tuto

            The training continue without any problem but the map and precision remains 0 all the process !!

            Ps : Here is the link of tuto i followed : https://github.com/ultralytics/yolov5/wiki/Train-Custom-Data

            ...

            ANSWER

            Answered 2021-Dec-04 at 09:38

            Running my code in colab worked successfully and the resulats were good. I think that the problem was in my personnel laptop environment maybe the version of pytorch i was using '1.10.0+cu113', or something else ! If you have any advices to set up my environnement for yolov5 properly i would be happy to take from you guys. many Thanks again to @alexheat

            Source https://stackoverflow.com/questions/70199621

            QUESTION

            scatter plot color bar does not look right
            Asked 2022-Mar-24 at 22:20

            I have written my code to create a scatter plot with a color bar on the right. But the color bar does not look right, in the sense that the color is too light to be mapped to the actual color used in the plot. I am not sure what is missing or wrong here. But I am hoping to get something similar to what's shown here: https://medium.com/@juliansteam/what-bert-topic-modelling-reveal-about-the-2021-unrest-in-south-africa-d0d15629a9b4 (about in the middle of the page)

            ...

            ANSWER

            Answered 2022-Mar-24 at 22:20

            The colorbar uses the given alpha=.3. In the scatterplot, many dots with the same color are superimposed, causing them to look brighter than a single dot.

            One way to tackle this, is to create a ScalarMappable object to be used by the colorbar, taking the colormap and the norm of the scatter plot (but not its alpha). Note that simply changing the alpha of the scatter object (scatter.set_alpha(1)) would also change the plot itself.

            Source https://stackoverflow.com/questions/71608280

            QUESTION

            using DelimitedFiles with title of the header
            Asked 2022-Mar-09 at 19:26

            When importing a .csv file, is there any way to read the data from the title of the header? Consider the .csv file in the following:

            I mean, instead of start_node = round.(Int64, data[:,1]) is there another way to say "start_node" is the one in the .csv file that its header is "start node i"

            ...

            ANSWER

            Answered 2022-Mar-09 at 19:08

            The most natural way is to use CSV along with the DataFrames package.

            Consider file:

            Source https://stackoverflow.com/questions/71414537

            QUESTION

            Pytorch : different behaviours in GAN training with different, but conceptually equivalent, code
            Asked 2022-Feb-16 at 13:43

            I'm trying to implement a simple GAN in Pytorch. The following training code works:

            ...

            ANSWER

            Answered 2022-Feb-16 at 13:43
            Why do we different results?

            Supplying inputs in either the same batch, or separate batches, can make a difference if the model includes dependencies between different elements of the batch. By far the most common source in current deep learning models is batch normalization. As you mentioned, the discriminator does include batchnorm, so this is likely the reason for different behaviors. Here is an example. Using single numbers and a batch size of 4:

            Source https://stackoverflow.com/questions/71140227

            QUESTION

            Is there a way to query a csv file in Karate?
            Asked 2022-Feb-02 at 03:20

            I am looking for a similar functionality like Fillo Excel API where we can do CRUD operations in an excel file using query like statements.

            A select statement in a csv file is a great addition to the framework to provide more flexibility in test data driven approach testing.

            Sample scenario: A test case that needs to have multiple data preparation of inserting records to database.

            Instead of putting all test data in 1 row or 1 cell like this and do a string split before processing.

            ...

            ANSWER

            Answered 2022-Feb-02 at 03:20

            There's no need. Karate can transform a CSV file into a JSON array in one line:

            Source https://stackoverflow.com/questions/70949738

            QUESTION

            Multi Processing with sqlalchemy
            Asked 2022-Feb-01 at 22:50

            I have a python script that handles data transactions through sqlalchemy using:

            ...

            ANSWER

            Answered 2022-Jan-31 at 06:48

            This is an interesting situation. It seems that maybe you can sidestep some of the manual process/thread handling and utilize something like multiprocessing's Pool. I made an example based on some other data initializing code I had. This delegates creating test data and inserting it for each of 10 "devices" to a pool of 3 processes. One caveat that seems necessary is to dispose of the engine before it is shared across fork(), ie. before the Pool tasks are created, this is mentioned here: engine-disposal

            Source https://stackoverflow.com/questions/70918448

            QUESTION

            Trouble changing imputer strategy in scikit-learn pipeline
            Asked 2022-Jan-27 at 05:26

            I am trying to use GridSearchCV to select the best imputer strategy but I am having trouble doing that.

            First, I have a data preparation pipeline for numerical and categorical columns-

            ...

            ANSWER

            Answered 2022-Jan-27 at 05:26

            The way you specify the parameter is via a dictionary that maps the name of the estimator/transformer and name of the parameter you want to change to the parameters you want to try. If you have a pipeline or a pipeline of pipelines, the name is the names of all its parents combined with a double underscore. So for your case, it looks like

            Source https://stackoverflow.com/questions/70873560

            QUESTION

            Does tensorflow re-initialize weights when training in a for loop?
            Asked 2022-Jan-20 at 15:12

            I'm training a model within a for loop, because...I can. I know there are alternative like tf.Dataset API with generators to stream data from disk, but my question is on the specific case of a loop.

            Does TF re-initialize weights of the model at the beginning of each loop ? Or does the initialization only occurs the first time the model is instantiated ?

            EDIT :

            ...

            ANSWER

            Answered 2022-Jan-20 at 15:06

            Weights are initialized when the layers are defined (before fit). It does not re-initialize weights afterward - even if you call fit multiple times.

            To show this is the case, I plotted the decision boundary at regular training epochs (by calling fit and then predict):

            Source https://stackoverflow.com/questions/70788383

            QUESTION

            How to force Pytest to execute the only function in parametrize?
            Asked 2022-Jan-20 at 14:32

            I have 2 tests. I want to run the only one:

            ...

            ANSWER

            Answered 2022-Jan-20 at 14:32

            It looks like that only something like that can resolved the issue.

            Source https://stackoverflow.com/questions/70721021

            Community Discussions, Code Snippets contain sources that include Stack Exchange Network

            Vulnerabilities

            No vulnerabilities reported

            Install tensorrt-yolov4

            You can download it from GitHub.
            You can use tensorrt-yolov4 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.

            Support

            For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .
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