Posenet resnet50lavori

I'm looking for a freelancer who can implement four separate deep learning models for deepfake image detection. The desired models are: - CNN - Vgg16 - Resnet50 - A fourth model of your recommendation Three datasets will be used for training and validation. I prefer the usage of FaceForensics++, CelebDF, DFDC, but I am open to other high-quality image datasets. The analysis of these models should include: - Accuracy evaluation - False positive and false negative analysis - Comprehensive comparison of model performance The freelancer has the freedom to prioritize the implementation of these models as they see fit. I am open to suggestions on the pros and cons of each model, and how they could serve my project best. In your proposal, I am particularly interested in a detailed...

...be used for image processing and understanding. Ideal skills and experience for this job include: - Proficiency in app development for both iOS and Android platforms - Experience in integrating A.I technology into mobile apps - Knowledge of data tracking and analysis techniques Things to be built 1 User Registration and Profile Management 2 Camera Integration 3 AI Algorithm linking such as ( Posenet or any other AI modal ) 4 Measurement Calculation 5 Recommandation to our ecommerce uniform (hyperlink) 6 Cross-Platform Development 7 Database Integration 8 User Authentication and Security 9 Testing and Quality Assurance 10 Integration with Payment Gateway (if needed / maybe no need as all payment is in e-com) 11 App Deployment to App Stores 12 Maintenance and Updates (per year h...

The deep learning models are trained on a dataset of bird sounds to learn the patterns and characteristics of different bird species. The dataset can be sourced from publicly available sources or collected by the developers of the system. The proposed system uses deep learning models ResNet50, Xception, and InceptionV3 for bird audio classification. These models have been shown to achieve high accuracy on image classification tasks and can be adapted for audio classification. The system is designed to be accessible through a mobile app. This means that users can record bird sounds using their phone's microphone and get real-time feedback on the bird species. The methodology for bird audio classification involved training a CNN model using three popular architectures, namely Re...

hello i have a project to detect POTHOLES in road and i want to use the code on my dataset in this site but it does not work with me this is the code page i am not expert in python so i want someone to help me to run it and do some modification on it

Hello, I need help to plot training and val accuuraccy and loss

AI Inferencing and Resnet50 project for a ZCU106 Evaluation Board.

...to look at the same image and then check their agreement. I do this because I would rather reject parts than have them sorted incorrectly. My images are 300x300. I look at the weight of the prediction, and 95% of my predictions are almost certain, say .99999, so I haven’t been able to do the simple thing of just looking at the strength of the prediction. In case this is relevant, the resnet50 classifier that I have trained might be overtrained. Within three epochs it is at like 99.7% accuracy with a val_accuracy of 98%. Epoch 3/3 99/99 [==============================] - 572s 6s/step - loss: 0.0138 - accuracy: 0.9967 - val_loss: 0.3574 - val_accuracy: 0.9796 Here is an article that shows what needs to be implemented.

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=resnet50.ResNet50(weights='imagenet',input_tensor...

Hi Daniel Mauricio V., need help with the code. Found a ready-made code, but I need to change a couple of things. Take another dataset (FER2013) and rework the code a bit, so it's not an exact copy. Also remove everything unnecessary like parser and other models(resnet18 and others). Only two networks need to be trained, ResNet50 and VGG16. I tried it myself but it is not trained well for some reason.

Hi Loyid A., need help with the code. Found a ready-made code, but I need to change a couple of things. Take another dataset (FER2013) and rework the code a bit, so it's not an exact copy. Also remove everything unnecessary like parser and other models(resnet18 and others). Only two networks need to be trained, ResNet50 and VGG16. I tried it myself but it is not trained well for some reason. Can you do the work? A very short turnaround time, literally a couple of days. And how much will it cost?

In Python, Keras, TF>2.4 I need a simple ResNet50-based image retrieval to be implemented. Then mean average precision based on this page: and precision-recall curve:

I want you to build a script that produces a trained model without pretraining using resnet50, I want you to use the VOC2012 dataset to train the model. Split the training data the first 12,000 for the training. I need this done by tomorrow

...ML scripts from GitHub to MLReef. To make them easly useful to our users while still keeping flexibilty and control. What is the task? 1. Find a ML function of your liking (can be as small as a data-preprocessing opertation to the newest Deel Learning Algorithm) and publish it successfully in MLReef. Take for example: GitHub: MLReef: There is a video tutorial on how to port a model. The fast explanation: you need to write decorators based on parameter arguments set by e.g. argparse or any other command line addressable argument function. 2. Show that it worked (via an experiment or data preprocessing or visualization). We will support you during the entire process. Depending on the code and level

**** INDIVIDUAL FREELANCERS ONLY **** Looking for an experienced Unity developer for ~ 1-2 month project to develop an app on Unity. High level project requirements (Detailed requirements to be provided once shortlisted) - - As a first step, create a quick proof-of-concept to demonstrate your skill level (related to the application requirements). T...duration contract once the MVP is completed. - Delivery and payments will be milestones based - Write - "I am human" at the top of your bid/response, so we know you have read through the job requirements Required experience - - Experience in game development - Minimum 6 years experience on Unity development (both Android and IOS) Good to have experience - - Tensorflow / Tensorflow Lite experience - PoseNet / OpenPose exper...

Need a tutor for machine learnin, must know how to use Wekinator, ML5, Posenet, Style Transfer , sound classification

Hi Kaibalya B., I want to update the existing PoseNet algorithm to OpenPose and extract to save metrics like body posepoints, UserID, time and activity to Json, csv like we did before. No changes except baseline algo which is OpenPose this time. I'll pass you my old notebooks which you developed for reference. thanks

Use both models(posenet and yoga) and show if the user is doing good. It must have a login and signup screen, and should allow the user to pick between diferent poses by their ability, begginer, intermediate and expert.

I need the ".pth" models exported by this project (which uses resnet50 as a base model) to be served by PyTorch serve. An example saved model is here: Deliverables: 1. A script that can take the .pth model and serve it with PyTorch serving. 2. A command-line script that can make inferences to the PyTorch serving service given an input image.

Hi, I am searching for a developer who can help me build a PyTorch dataset for language segmentation. A lot of the dataset is already finished. There a...remove `getTopNCharacters2Dict()` use entire corpus instead * create png and csv from pytorch dataset (see ``) * check if number of lines is random ## Implement Faster-RCNN/Mask-RCNN * use pytorch faster-rcnn to get bounding boxes for each language (class is either chinese or english; will be extended lateron) * * (check what is based on faster-rcnn) * build translation stage on-top of roi-align stage in mask rcnn (need to further think about it; first dataset needs to be completed)

we are doing a project on retinopathy image detection , but our guide wants us to use a neural network which is not pre trained , we used resnet50 which our guide rejected. we need the project to be done using a convolutional neural network which is not pretrained.

Help us build a unique app. It involve in recording and editing a video + using core ML- PoseNet

...sizes (parameter image size..., of course, must fit to the models above) - Image preprocessing should be done via Keras preprocess_input, e.g with tf.keras.applications.resnet.preprocess_input for ResNet50 - Data augmentation should be possible via the network, e.g. data_augmentation = ([('horizontal_and_vertical'), (0.02, 0.02)] x = data_augmentation(input) x = preprocess_input(x) ... It should be possible to switch data augmentation on and off (e.g. on for train data, off for test data) - In the example please use ResNet50 with data augmentation 4) Head network - Should be exchangable easily (function create_head_model(embedding_shape)) 5) Training - Callback functions should be used - Models should be saved -

deep learning project(cnn architecture inceptionv3 or resnet50 or 152) for breast cancer detection using Jupyter notebook .There is existing code need to do modification and improve accuracy In addition user interface if possible.I have datasets in histopathology and mammogram. existing Code: httpss://

...pose understanding. We are looking to accelerate our effort with the help of a TensorFlow/TensorFlow Lite expert to work with us on model tuning and optimization. Some experience working with Swift/iOS is required. We expect to have ongoing work for this project. This would be your first task: Google published a web based model for pose detection based on a ResNet50 architecture: This model is only available as a tensorflow js. model and we would like to convert it to a tensorflow lite model running on an iOS app. We will provide with the iOS app (currently running on another model) - which is a simple app that simply loads videos and runs models on them. There is no significant mobile development outside adapting the model inputs

is looking for an expert web developer to build an embeddable WebGL component and custom landing page that leverages markerless feature tracking and WebGL to deliver an interactive 3D experience in real time. [ required experience ] * WebGL site development experience * Experience with with real time markerless feature detection and related libraries (PoseNet, MediaPipe, ) * Source control experience is a must (GITHUB preferred) [ skills ] * Ability to communicate clearly * Attention to details * Easily legible coding and documentation style

Hello. I need to translate custom TensorFrow model based on ResNet50 to TensorRT, so it works in Jetson Nano.

Need a python code preferably a .pynb notebook to train a CNN model one for ResNet50 and one for VGG16 or VGG 19. The code must be provided with information on all the hyperparameters The Data source Trained model Accuracy model learning graphs comparison of both the models

hello I have a ready video dataset divided into two categories: violence and non-violence, the dataset is 2GB. 1)I want a CNN model that will be able to detect the violence percentage is preferred to be above 94% 2)Please use some of the pre-trained CNN models such as resnet50 and VGG16 3)I want it to be a video-level classification, not image-level classification; this critical you must know the difference. 4)I want you to include the graphs of the module trained and tested 5)I want you also to include the performance metrics 6) the result of the train and test is very 7)80% training and 20% for testing

Need to do the following things Datasets to be use 1. ESC-50( Environmental Sound Classification) 2. UrbanSound8K Models to be use 1. ResNet50 2. DenseNet 3. Inception The following are the references for Github code 1. 2. kamalesh0406/Audio-Classification: Pytorch code for "Rethinking CNN Models for Audio Classification" () What I want to do..? is that I have to implement the methods and in the kemalesh0406 code. So in kamalesh0406 code I will do preprocessing to get spectrograms of all two datasets the code for making spectrograms is already given. Then in file in MER code I will call these datasets and using above three mentioned model to train these datasets. How I will train these datasets..? First do normal training

I am looking to find a way to create an infant model, and I need to train. The script needs to be built to train the model, and subsequently use it as a model just like ResNet50. Won't take long if you are truly an expert.

project: I have a 2D medical imaging dataset with 3 classes and 5000 images per class.. the job is to train Vgg-19 and ResNet50 deep networks on this and also GRAD-CAM to visualise the learned features. resources: i will of course provide data and general instructions.. you will code on google colab and classification accuracy should be above 80% time and cost: limit is 1 week but earlier the better... budget is 10,000 INR in 2 milestones Milestone 1: (worth 5000 INR) get at least 80% classification accuracy on Vgg-19 and ResNet50 Milestone 2: (worth 5000 INR) implement learned feature visualisation using GRAD-CAM the data can be found at:

Dear Ahmad, I noticed your profile (and one of your Youtube videos actually) and would like to see if you could help with a project. It's basically about implementing a function I have created to a convolutional neural network. Let me know if you can discuss via chat. Thank you for your attention ! I am using the trainNetwork function (with resnet50). To summarize, I wrote a function that selects 35 random images from my entire training image datastore (which has 2000 images approximately) with their labels. I basically want to use my function in order to create batches throughout the training process. For example, let's say I have 60 iterations per epoch, I would like to run my function 60 times / epoch to get a random miniBatch at every iteration (according to my func...

hello, We have a customized the tensorflow js (posenet model) and we want to make it available offline (not connected to internet). The online page is available here: The complete project (javascript+ html) is available in the attached file. Thanks

I am looking for ml5 and posenet expert to work on my project. More details will be shared with selected freelancers

Pose Estimation Xamarin IOS (Posenet, Openpose etc) I need this Swift Posenet sample converted to be consumed by Xamarin IOS Deliverables The xamarin ios app needs to be fully functional as the swift app.

I need this Swift Posenet sample converted to be consumed by Xamarin IOS Deliverables The xamarin ios app needs to be fully functional as the swift app.

I need you to convert this app to xamarin ios.

I need this Swift Posenet sample converted to be consumed by Xamarin IOS I am a Xamarin C# developer however i don't have Swift skills. Deliverables The xamarin ios app needs to be fully functional as the swift app.

I need this Swift Posenet sample converted to be consumed by Xamarin IOS The xamarin ios app needs to be fully functional as the swift app.

I need this code transported to C# Xamarin IOS

Using TensorFlow and Posenet I am looking for something that can track Eyes Head Shoulders Arms Elbows Waist Thighs Knees Ankles Feet And I would like sometime that can use multi-camera for more accuracy And something that can create a 3D skeleton tracking if the person

I need someone that can get a Posenet Tensorflow human pose estimation model working correctly for this project that can track body movements standing upright and on the ground as well. For instance, doing a pushup where some of the body limbs are possibly occluded.

Seeking expressions of interest to work with an Online Physiotherapy Business to integrate PoseNet pose estimation overlays over static-pose images. For example, a user/client/patient uploads a static image of their posture from in front, the side and from behind. The PoseNet library will load the image data and process the image to overlay the skeleton/bones accordingly. I have provided examples in the attached word document below. I intend to embed/integrate the finalised images into a report for dissemination. I will provide more information upon request.

I need a detection (and more things) app for both platforms in 400usd. Must have good reviews.

This project generally deals with the recognition of gestures that are further used to control the pointer while playing the game. Any body part can be used to control the object by linking that object to the pointer accordingly. This is done with the help of Google’s library for machine learning, Posenet pose detection model, a video or webcam, a browser that supports latest javascript features, and internet connection to load the libraries at runtime. We have created a local server to host this WEB APP and perform all the detection on that.

I want to develop some server-side code Using PoseNet,/OpenCV/Yolov3 and Python ✓ Analyse a video of a football match. For each player, I want to generate some stats Deep experience of the subject area is a must. No time wasters please. In both cases, you will need to show me what you have done in this field, and prove that you can deliver the serverside code in Python. To prove that you have read this, please start your bid with the word "Footie". Thank you.

I am trying to modify a piece of code which already has a Resnet50 and change it into a Resnet34. I have modified the encoder function but i get an error when i make the residual block. The main difference between Resnet34 and Resnet50 is the former is 2 layers deep compared to the latter being 3 layers deep. Therefore i get an error relating to " Dimensions must be equal, but are 64 and 128.." Attached, you can find the original code which i want to base it off. Also my modified code where i tried removing ch[2] to make sure it has 2 layers deep.

App proposed budget is 500usd. Android and iOS. Developer must publish iOS version.

I need a virtual gym app using tensorflow posenet.

App proposed budget is 250usd. Developer must publish iOS version.