Densenet pytorch jobs
Hello folk, We want o build a Federated Learning and Homomorphic Encryption-based framework for Computer Vision. We will provide complete guidance about the implementation and possibly give a few codes in PyTorch. We can discuss any details over chat. Note: The budget is negotiable.
I want to concat a new Model (Keras code) with present model (Maybe It will be easy)
Development of bespoke / custom deep-learning-based AI solutions for computer vision applications operating on iot edge device (smart cameras, satellites, home security, logistics, transportation, etc.). Pytorch, TFLite, deep learning, object detection, classification, segmentation, non-standard custom models.
I want someone to compile and run the below codes, provide me with pre-trained models, test on custom datasets, Run Evaluate_PSNR_SSIM to obta...Super-Resolution Link: Residual Laplacian Super-resolution Link: Network for Image Super-Resolution Link: 9. Image Super-Resolution Using Very Deep Residual Channel Attention Networks Link: 10. RDN Link: the model must be trained if there is no pre-trained model in the repo and then saved models should be saved in order to run the test on my custom images all details (updated code, test results, pre-trained models, evaluation) should be provided
I have one python work which needs to be done asap. I will share the details in inbox. please bid.
Hi I want to change open source project code about input data with additional encoder I can give you some codes which i want to use. 1. input data conversion codes 2. Encoder codes
I want someone to compile and run the below codes, provide me with pre-trained models, test on custom datasets, Run Evaluate_PSNR_SSIM to obta...Super-Resolution Link: Residual Laplacian Super-resolution Link: Network for Image Super-Resolution Link: 9. Image Super-Resolution Using Very Deep Residual Channel Attention Networks Link: 10. RDN Link: the model must be trained if there is no pre-trained model in the repo and then saved models should be saved in order to run the test on my custom images all details (updated code, test results, pre-trained models, evaluation) should be provided
The project concerns the classification of the music instrument data: " kaggle datasets download -d aayushme/music-instruments-classification " using ResNet-50 from scratch (no transfer learning). I need codes written for CPU and GPU with Keras (no Pytorch).
Tpc_fuser , pytorch, tensor flow, and Ml models resnet,bert, algorithms
Tpc_fuser , pytorch, tensor flow, and Ml models resnet,bert, algorithms
I need help adding a file to Anaconda. I do not know how to add this. Here are the instructions below from jamescalam/transformers Using Download the for the course. In Anaconda prompt, navigate to the directory containing the and write conda env create -f environment.yaml. Activate the new environ...Anaconda. I do not know how to add this. Here are the instructions below from jamescalam/transformers Using Download the for the course. In Anaconda prompt, navigate to the directory containing the and write conda env create -f environment.yaml. Activate the new environment with conda activate ml. Move onto the Installation of PyTorch section.
...deep learning) and natural language processing (TFIDF, text classification, word embeddings, language models), demonstrated by the ability to dig deep into practical problems and choose the right ML method to solve them Solid Python programming skills to quickly prototype, as well as develop, projects into production. Experience with any modern machine learning frameworks such as Scikit-Learn, Pytorch, Tensorflow, or Spacy is highly desirable. The experience acquired in an academic setting is acceptable. Experience working with large structured or unstructured data sets and running exploratory data analysis. Experience with MongoDB is not required but is a plus. Experience with Databricks is a plus. Good communication skills, including the ability to present and communicate machi...
A startup that develops and sells image analysis web applications ,develop of microscope hardware, in the medical, life sciences, and industrial fields. The technologies I want are vue.js, React, docker, fast api, json, Azure, GCP, tensorflow, u-net, pytorch, caffe, and so on. We want developers who are collaborative, communicative, and responsive. The working time zone depends on JST. We are looking for friends who can sympathize with our philosophy.
OMG I just reapaired PC my GPU burned I had to replace it. and after that notebboks stopped to work. I got such problem when running a training tried to follow also But i am getting only pip errors. would you helo me with that I am totally stucked....I need help ASAP I need help via AnyDesk
A startup that develops and sells image analysis web applications ,develop of microscope hardware, in the medical, life sciences, and industrial fields. The technologies I want are vue.js, React, docker, fast api, json, Azure, GCP, tensorflow, u-net, pytorch, caffe, and so on. We want developers who are collaborative, communicative, and responsive. The working time zone depends on JST. We are looking for friends who can sympathize with our philosophy.
...Current cutting-edge technologies and future technologies. Bias and/or privacy. How deep learning techniques are helping/injecting various kinds of biases, or securing/endangering privacy. New deep learning technologies (that support deep learning computation). Hardware and devices (e.g. accelerators, chips, clusters), systems and computing models (e.g. distributed deep learning), libraries (e.g. PyTorch, Caffe, , etc.) Requirements: 1000 - 1200 words, plus references. The paper must have minimally the following clearly labeled sections: A. Introduction/overview, B. Literature review, including summaries (in your own words, of course) of at least two specific examples/articles, emphasizing the most important points, C. Discussions and your comments, and D. Conclusions. E. List of...
I have a simple python/keras/resnet50 script to train an image classification model. The resnet50 part is like 40 lines of code. I need someone to port it to pytorch. Below is the heart of the script that needs to change. If you know pytorch, this should be easy to do. This is not the whole script, but if you can show me reason to believe you can do this, I will share the script with you. A successfully completed project will run an entire script with the resnet50 model. The script as it exists with keras does this: load the training and validation data and labels build and compile model train (fit) model build accuracy matrix input_layer=(shape=(nrows,ncolumns,channels)) resnet_model=(weights='imagenet',input_tensor=input_layer,include_top=False)
Hii, To make model robust by using adversearial training, Model: Alexnet, Lenet Dataset: cifar10 Framework: pytorch
I would like to convert some optimization (second-order non convex optimization) PyTorch code to C++. Ideally the code will also implement a supporting package which is imported and have CUDA support, but willing to fund work where the code uses an alternative optimizer like LBFGS and versions with no GPU parallelization support. Also interested in multiprecision support if possible. Rate negotiable depending on ability to tend to details above.
I would like to convert some optimization (second-order non convex optimization) PyTorch code to C++. Ideally the code will also implement a supporting package which is imported and have CUDA support, but willing to fund work where the code uses an alternative optimizer like LBFGS and versions with no GPU parallelization support. Also interested in multiprecision support if possible. Rate negotiable depending on ability to tend to details above.
Hi Vasilatos. My goal is to improve the performance of some pytorch code in any way I can. If I can get a significant time improvement by switching to C++, I would be interested in having you rewrite it there. I'm willing to pay you to implement it in C++. What would be your rate on this with and without gpu parallelization? (e.g. with and without CUDA support, since I am still interested in cpu timing enhancement)
Looking for someone to modify a python script to add a new function. The script utilizes pyTorch to generate models based on a dataset of images. The script has a function to generate interpolation between two random spaces in the model and makes a gif of the result. I am looking for someone to implement a circular interpolation of said function so as to generate a seamless looping gif the code can be found here: the function can be found here: (def generate_interpolation) I would like the function to operate the same (save frames, num steps, etc) however the result will be a seamlessly looping gif (circular interpolation), I have examples from other
we need a developer that will help us in the deployment of computer vision and deep learning solutions into a server. Some of the desired skills for this job are: - Linux Ubuntu - Python - Pytorch and Tensorflow - Docker - REST, Flask or Django - XML, JSON, SQL SSH
Need someone with experience in reinforcement learning to help me with my project. - Building extensions of an existing algorithm based on another implementation - testing the performance on different Pybullet environments - Requires extensive knowledge of PyTorch and actor-critic models Need to build an extension of an existing algorithm based on the attached paper
I want to implement Faster R-CNN Pytorch on my custom dataset.
please see the attached file to have better description in this project, you will need to train a simple Logistic Regression model. You can use any machine learning library that supports distributed training, such as Tensorflow and PyTorch. You will start with writing the code for training the model on a single machine. Training should start from a random linear vector as your model. Then, calculate the loss of your model on the dataset using: , where and are training data features and label, respectively. The dataset for you to train your model is MNIST handwritten digits database. Train to minimize with an optimizer such as gradient descent. The next task is to modify the workloads so that they can be launched in a distributed way. You will experiment with both synchrono...
Specifics: Although I use tensorflow, I need a VMWare player Ubuntu 22.04LTS image that also supports ONNX and pytorch. To that end, the specifics of this project are that the freelancer will: 1. Download a 'clean' Unbuntu 22.04LTS vmdk from , and run it on the free VMWare player. (This will remove any preinstalled dependencies) 2. Download, install and build pytorch and Onnx, and all dependencies, while recording all commands used to perform this task 3. Verify the builds of pytorch and Onnx by converting a small pytorch model to ONNX 4. Download, install and build TensorFlow, and all dependencies, while recording all commands used to perform this task 5. Verify the build of Tensorflow by converting a small ONNX model to TensorFlow Deliverables, ...
Implement gradient accumulation on batch_size = 2 is currently set at , ideally would like to only update the model at > the 10th iteration (or 100th iteration as an example).
I need 2 TorchScript PyTorch .PT files and accompanying v1.9.0 metadata into an ONNX format needed for a C# project.
Preparing datasets for training ● Find public data and/or restructure data suitable for the project ● Responsible for design and development of different types of computer vision models that fits the requirement. ● Understanding of different data structures and ability to convert from structure to another ● Understanding of different Deep Learning Libraries (eg. Tensorflow, PyTorch, openvino etc) ● Create functions for training and inference ● Test the inference time on different types of servers/GPUS/CPUs/Edge devices ● Build ML modules, along with accuracy, must also deliver the production workload expectations - work with real world data, suitable inference time, compatibility with tech-stack, work on CPUs where applicable ● Understand different types of ML problems - classificat...
Hi, I've this Google Colab script that is taking few parameters of user input and produces 500x500px png output. The code blocks now are excecuted pressing manually play and waiting for the script to finish, then changing a string of input field, and pressing play again. Each ...with "-" dashes. Both auto-download or saving in google Drive are okay. Before bidding you should be sure to be able to work with python projects including all these libraries: - Argparse - Augmentation - Einops - Exempi - Imageio - Imgtag - IPython - Json - Kornia - Libxmp - Lsb - Math - Models - Notebook - Numpy - Omegaconf - OmegaConf - Optim - Path - Pathlib - Pillow - Python-xmp-toolkit - Pytorch-lightning - Stegano - Sys - Taming - Torch - Torchvision - Tqdm - Transforms - Wget Le...
I have a project wherein I want to calculate accuracy of Pytorch Model. I am using kaggle notebook. Actually I wanted to calculate the accuracy of the model and if required I wanted to improve the model for better accuracy, also want to have a code walk thru. URL -
I am working on combining a U-Net (model) with a Vision Transformer (model) to achieve the task of removing weather-based noise from input images (rain, snow, fog). My method trains a little bit and stop after few initial epochs then reports error in computing the first PSNR and SSIM metrics. I can't seem to figure out the problem. At this point I need...(model) to achieve the task of removing weather-based noise from input images (rain, snow, fog). My method trains a little bit and stop after few initial epochs then reports error in computing the first PSNR and SSIM metrics. I can't seem to figure out the problem. At this point I need help to make the model train successfully and achieve good results. Freelancer with good knowledge of Python3, PyTorch, and deep learning ...
Hi Aditya, Do you have experience with CUDA? I am looking to port over a small parallelized optimization procedure from PyTorch to CUDA. I think for someone with experience with these languages this should take a couple hours or less. I'm willing to negotiate on the rate though. Best,
Hi Usama, Do you have experience with CUDA? I am looking to port over a small parallelized optimization procedure from PyTorch to CUDA. I think for someone with experience with these languages this should take a couple hours or less. I'm willing to negotiate on the rate though. Best,
Hi Milind, Do you have experience with CUDA? I am looking to port over a small parallelized optimization procedure from PyTorch to CUDA. I think for someone with experience with these languages this should take a couple hours or less. I'm willing to negotiate on the rate though. Best,
Hi Loyid, Do you have experience with CUDA? I am looking to port over a small parallelized optimization procedure from PyTorch to CUDA. I think for someone with experience with these languages this should take a couple hours or less. I'm willing to negotiate on the rate though. Best,
Hi Mohamed, Do you have experience with CUDA? I am looking to port over a small parallelized optimization procedure from PyTorch to CUDA. I think for someone with experience with these languages this should take a couple hours or less. I'm willing to negotiate on the rate though. Best,
Hi Shivam, Do you have experience with CUDA? I am looking to port over a small parallelized optimization procedure from PyTorch to CUDA. I think for someone with experience with these languages this should take a couple hours or less. I'm willing to negotiate on the rate though. Best,
High-quality ski...lassification/data and Current Project Status: The code pipeline is working properly. Code is already implemented in PyTorch. The code is written such that it also saves the progress after every epoch. Therefore, there is no tension of runtime interruptions. You can refer to Current requirements: Hyperparameter tuning or changes in the already implemented architecture is required for high-quality image generation and for reducing loss. Deliverables: 1. Edited colab code(PyTorch). 2. Results (Metrics used in conditional gans). 3. High-quality generated Images (Binary class Melonama and Non-Melonama). Please contact me so that I share the code.
We're looking for a freelance Senior Data Scientist (5+ years experience) for a 3 month project who speaks native Thai.
You need to convert a PyTorch notebook to Keras. Without errors. It comes from a prestigious book and it is 100% correct.
Transfer Learning When we have smaller datset, it is benefiical to use transfer learning--training on a larger dataset and then use that pretrained model to finetune on smaller dataset. Here, your task is to use transfer learning to predict house prices from images. Libraries allowed: Basic python, numpy, and PyTorch. Note: Submit the jupyter notebook and its pdf export. Before uploading to Canvas, make sure that all commands in your jypyter notebook are executed, and outputs, plots, and figures are visible. a) Download SoCal dataset from Kaggle Put first 12000 images under "train/images" in your local directory and the rest under "test/images". Create label filtes for training and test and put them in the respective folder
In this bonus project, you will be fine-tuning a pre-trained model of your choice on the task of t...project, you will be fine-tuning a pre-trained model of your choice on the task of token classification in the cybersecurity domain. This task is essentially the same as the token classification example presented in this module, with the difference that you will be fine-tuning on a custom dataset. The dataset is available here: Download . Please complete this task using PyTorch on Google Colab, and feel free to use any 3rd-party library (incl. HuggingFace Transformers) in your implementation. Submission: A link to your Google Colab notebook. Please make sure that the link sharing option is set to "anyone with link", otherwise I will not be able to access your noteboo...
Looking for a implementation in python of the above mentioned paper with ResUTNet-50. More info can be found at this git: For the joint learning part, refer to this: The main change the coder should make is use Split-and-Merge EMA instead of EMA for feature aggregation. Relevant papers are attached. Also interested in demonstration of alternate squeeze-and-excitation blocks effect on performance but that's not a necessity. Please reach out only with confidence. The last person didn't deliver and cost me time.
Create a code sample that uses PyTorch Lightning and sstack ( 3rd party library ) to train a simple model Requirements: 1. It’s allowed to use one of the existing examples provided by PyTorch Lightning from their documentation or repository (e.g. MNIST). You just need to adapt it to run with sstack. 2. The sample should allow running the training workflow without GPU, with a single GPU, and with multiple GPU. For example, you can use a sstack variable to control it. 3. Be sure to check that the training actually works in all cases (with a single GPU, with multiple GPUs, and with no GPUs). Sstack is basically allows you to automate training workflows, version and reuse data and models using a cloud vendor of your choice. We will be using AWS cloud service for this
