id stringlengths 7 11 | source stringclasses 1
value | category stringclasses 11
values | title stringlengths 15 214 | text stringlengths 70 30.5k | url stringlengths 57 160 | tags stringlengths 3 113 | created_at int64 1.22B 1.79B |
|---|---|---|---|---|---|---|---|
se_78802177 | stackoverflow | MACHINE_LEARNING | GPU performance worse than CPU performance on YOLO inferences | GPU performance worse than CPU performance on YOLO inferences
I am using the YoloDotNet NuGet package to test the performance of YOLO models. I'm doing this testing for my degree thesis. However, I have encountered an issue where the GPU performance is significantly worse than the CPU performance.
The problem is that... | https://stackoverflow.com/questions/78802177/gpu-performance-worse-than-cpu-performance-on-yolo-inferences | c#, machine-learning, deep-learning, gpu, yolov8 | 1,722,105,228 |
se_74604682 | stackoverflow | MACHINE_LEARNING | Identifying mushrooms through deep learning | Identifying mushrooms through deep learning
I need to write a program that recognizes mushroom species using deep learning. So far I have 26 mushroom folders, approx. 500 photos per species. The problem is that it receives a maximum efficiency of about 45%. Does anyone know what I could improve or what layers to put i... | https://stackoverflow.com/questions/74604682/identifying-mushrooms-through-deep-learning | python, tensorflow, deep-learning | 1,669,658,254 |
se_64095121 | stackoverflow | MACHINE_LEARNING | 6D pose estimation of a known 3D CAD object with limited model training for a new object | 6D pose estimation of a known 3D CAD object with limited model training for a new object
I'm working on a project where I need to estimate the 6DOF pose of a known 3D CAD object in a single RGB image - i.e. this task: https://paperswithcode.com/task/6d-pose-estimation. There are several constraints on the problem:
Us... | https://stackoverflow.com/questions/64095121/6d-pose-estimation-of-a-known-3d-cad-object-with-limited-model-training-for-a-ne | deep-learning, computer-vision, real-time, object-detection, cad | 1,601,259,258 |
se_78819334 | stackoverflow | MACHINE_LEARNING | How compute correlation between images | How compute correlation between images
I try to compute correlation between classes. The dataset involves several folders which are named by class. Each folder includes several images, I have used the below code to input images and labeling it with several classes
# Specify root path
root_path = './Datasets_1'
... | https://stackoverflow.com/questions/78819334/how-compute-correlation-between-images | python, deep-learning, correlation | 1,722,492,042 |
se_78810649 | stackoverflow | MACHINE_LEARNING | Tensorboard failed to load runs only in time series tab | Tensorboard failed to load runs only in time series tab
I'm building models using pytorch on Ubuntu platform. I use tensorboard (torch.utils.tensorboard / tensorboardX) to log training informations. I access these logs on windows Chrome browser. Scalars, histograms, etc. are showing normally, but timeseries shows noth... | https://stackoverflow.com/questions/78810649/tensorboard-failed-to-load-runs-only-in-time-series-tab | deep-learning, pytorch, artificial-intelligence, tensorboard | 1,722,329,160 |
se_78815544 | stackoverflow | MACHINE_LEARNING | How to correctly save a fine tuned model using apple MLX framework | How to correctly save a fine tuned model using apple MLX framework
We're using MLX to fine tune a model fetched from hugging face.
from transformers import AutoModel
model = AutoModel.from_pretrained('deepseek-ai/deepseek-coder-6.7b-instruct')
We fine tuned the model with command like python -m mlx_lm.lora --config l... | https://stackoverflow.com/questions/78815544/how-to-correctly-save-a-fine-tuned-model-using-apple-mlx-framework | python, machine-learning, deep-learning, large-language-model | 1,722,418,534 |
se_75124641 | stackoverflow | MACHINE_LEARNING | How to create add gaussian noise on an image | How to create add gaussian noise on an image
I want to create a function to add gaussian noise to a single input that I will later use.
I'm using the imageio module in Python.
def gaussian_noise(x, var): | https://stackoverflow.com/questions/75124641/how-to-create-add-gaussian-noise-on-an-image | python, python-3.x, deep-learning, pytorch | 1,673,781,362 |
se_33786879 | stackoverflow | MACHINE_LEARNING | Crude image clustering using a Caffe model? | Crude image clustering using a Caffe model?
Let's say I have a Caffe Model that can recognize textures. Is there a straightforward way to get a crude segmentation of an image using the classification results for a sliding window? | https://stackoverflow.com/questions/33786879/crude-image-clustering-using-a-caffe-model | deep-learning, computer-vision, caffe, image-segmentation | 1,447,868,897 |
se_66928939 | stackoverflow | MACHINE_LEARNING | How solve the error 'ValueError: cannot reshape array of size 10 into shape (6)'? | How solve the error 'ValueError: cannot reshape array of size 10 into shape (6)'?
I want to train FairMOT
https://github.com/ifzhang/FairMOT
and I have this error, Traceback is this.
Traceback (most recent call last):
File "train.py", line 98, in <module>
main(opt)
File "train.py", line 69, in main
... | https://stackoverflow.com/questions/66928939/how-solve-the-error-valueerror-cannot-reshape-array-of-size-10-into-shape-6 | python, deep-learning, pytorch, computer-vision, object-detection | 1,617,436,855 |
se_67865127 | stackoverflow | MACHINE_LEARNING | Using perspective transformation to change point of view of an image. Not getting desired result | Using perspective transformation to change point of view of an image. Not getting desired result
I am trying to change the perspective of the first image according to the second image. For finding the homography matrix I have found the four coordinates of a common object(white notice board) in both images.
Image 1
Ima... | https://stackoverflow.com/questions/67865127/using-perspective-transformation-to-change-point-of-view-of-an-image-not-gettin | python, opencv, deep-learning, computer-vision | 1,623,030,863 |
se_72461845 | stackoverflow | MACHINE_LEARNING | Reading files with .h5 format and using it in dataset | Reading files with .h5 format and using it in dataset
I have two folders( one for train and one for test) and each one has around 10 files in h5 format. I want to read them and use them in a dataset. I have a function to read them, but I don't know how I can use it to read the file in my class.
def read_h5(path):
... | https://stackoverflow.com/questions/72461845/reading-files-with-h5-format-and-using-it-in-dataset | python, deep-learning, pytorch, computer-vision, h5py | 1,654,086,286 |
se_42931850 | stackoverflow | MACHINE_LEARNING | are there any solutions or algorithms for detecting liquid in computer vision? | are there any solutions or algorithms for detecting liquid in computer vision?
This question just came up in my mind with curiosity.
So my question is that are there any solutions or algorithms detecting liquid such as water, coffee or something like this.
What I would like to do with this is just define whether it is... | https://stackoverflow.com/questions/42931850/are-there-any-solutions-or-algorithms-for-detecting-liquid-in-computer-vision | algorithm, deep-learning, computer-vision | 1,490,111,093 |
se_69831793 | stackoverflow | MACHINE_LEARNING | My code does not run on multiple GPUs in PyTorch | My code does not run on multiple GPUs in PyTorch
I used Faster R-CNN of PyTorch to train it on a dataset. It works well with one GPU. However, I have access to a system with 4 GPUs. I want to use 4 GPUs. However, when I check GPUs usage, only one GPU is used.
I select device in this manner:
if torch.cuda.is_available(... | https://stackoverflow.com/questions/69831793/my-code-does-not-run-on-multiple-gpus-in-pytorch | deep-learning, pytorch, computer-vision, gpu | 1,635,973,993 |
se_77105006 | stackoverflow | MACHINE_LEARNING | Conditional VAE ignoring conditional variables | Conditional VAE ignoring conditional variables
I am training a conditional VAE on a timeseries datase. Although my model is training well as evident by the small training and validation loss. however while generating samples, my model completely ignores the conditional variables and it looks like that it only generate... | https://stackoverflow.com/questions/77105006/conditional-vae-ignoring-conditional-variables | deep-learning | 1,694,695,402 |
se_56076445 | stackoverflow | MACHINE_LEARNING | How to make CNN learn positional constraints? | How to make CNN learn positional constraints?
I am working on image segmentation problem in medical domain using fully connected CNN.
The problem is that for particular image, it could have a lot of similar structures. Our task is to find the correct one. One thing that I'd like to make the CNN learn is that there sh... | https://stackoverflow.com/questions/56076445/how-to-make-cnn-learn-positional-constraints | deep-learning, computer-vision, conv-neural-network | 1,557,486,569 |
se_65827031 | stackoverflow | MACHINE_LEARNING | Pytorch Global Pruning is not reducing the size of the model | Pytorch Global Pruning is not reducing the size of the model
I am trying to Prune my Deep Learning model via Global Pruning. The original UnPruned model is about 77.5 MB. However after pruning, when I am saving the model, the size of the model is the same as the original. Can anyone help me with this issue?
Below is t... | https://stackoverflow.com/questions/65827031/pytorch-global-pruning-is-not-reducing-the-size-of-the-model | python, deep-learning, pytorch, computer-vision, pruning | 1,611,230,613 |
se_71112708 | stackoverflow | MACHINE_LEARNING | Image blur detection with google vision ai | Image blur detection with google vision ai
Is it possible to train a model that will detect cctv camera abnormally:
Camera blur (defocus)
Camera blocking (black image or blocked image)
Thanks | https://stackoverflow.com/questions/71112708/image-blur-detection-with-google-vision-ai | deep-learning, computer-vision | 1,644,845,398 |
se_76463896 | stackoverflow | MACHINE_LEARNING | Grad-cam always placing the heatmap in the same area | Grad-cam always placing the heatmap in the same area
Here is the part of my code relevant to the issue:
def forward_hook(module,input,output):
activation.append(output)
def backward_hook(module,grad_in,grad_out):
grad.append(grad_out[0])
model.layer4[-1].register_forward_hook(forward_hook)
model.layer4[-1].... | https://stackoverflow.com/questions/76463896/grad-cam-always-placing-the-heatmap-in-the-same-area | python, deep-learning, pytorch, computer-vision | 1,686,651,645 |
se_76730888 | stackoverflow | MACHINE_LEARNING | Why is my MLP-GRU model's train and validation accuracy is so low? | Why is my MLP-GRU model's train and validation accuracy is so low?
My task is action recognition where my inputs are mediapipe keypoints. I have 300 imbalanced classes. The first few classes have over 500 samples while the majority have less than 20 so I am using WeightedRandomSampler to deal with this imbalance. ... | https://stackoverflow.com/questions/76730888/why-is-my-mlp-gru-models-train-and-validation-accuracy-is-so-low | python, deep-learning, pytorch, computer-vision | 1,689,863,114 |
se_68879419 | stackoverflow | MACHINE_LEARNING | Emotion Detection with FER2013 and MPI dataset using CNN and TFLearn | Emotion Detection with FER2013 and MPI dataset using CNN and TFLearn
I am just beginner for Deep Learning. I try to capture all details.
Perplex is derived from MPI dataset. other emotions are derived from FER2013. To balance the data set, all emotions into (training: 3171, validation: 816) strategy, due to lack of pe... | https://stackoverflow.com/questions/68879419/emotion-detection-with-fer2013-and-mpi-dataset-using-cnn-and-tflearn | deep-learning, computer-vision, conv-neural-network, kaggle, tflearn | 1,629,618,778 |
se_78806266 | stackoverflow | MACHINE_LEARNING | Some layers of my designed deep learning model are initialized in the model class but are not used in the forward process,which cause different result | Some layers of my designed deep learning model are initialized in the model class but are not used in the forward process,which cause different result
Some layers of my designed deep learning model are initialized in the model class but are not used in the forward process. I found that when the code of these layers ar... | https://stackoverflow.com/questions/78806266/some-layers-of-my-designed-deep-learning-model-are-initialized-in-the-model-clas | python, deep-learning, pytorch | 1,722,244,802 |
se_75096662 | stackoverflow | MACHINE_LEARNING | Pytorchvideo Models Resnet Input shape | Pytorchvideo Models Resnet Input shape
I am using the following code to load resnet50 but since this is a video. I am not sure what is the expected input. Is it ([batch_size, channels, frames,img1,img2])?
Any help would be fantastic.
import pytorchvideo.models.resnet
def resnet():
return pytorchvideo.models.resnet.... | https://stackoverflow.com/questions/75096662/pytorchvideo-models-resnet-input-shape | python, deep-learning, pytorch, model, computer-vision | 1,673,528,221 |
se_74986249 | stackoverflow | MACHINE_LEARNING | CNN-LSTM performance identical to LSTM, is there a mistake in my code? (Pytorch) | CNN-LSTM performance identical to LSTM, is there a mistake in my code? (Pytorch)
I am trying to recreate the models from a study in which CNN-LSTM outperformed LSTM, but my CNN-LSTM produces nearly identical results to the LSTM. So it seems like the addition of the convolutional layers is not doing anything. The study... | https://stackoverflow.com/questions/74986249/cnn-lstm-performance-identical-to-lstm-is-there-a-mistake-in-my-code-pytorch | deep-learning, pytorch, neural-network, conv-neural-network, lstm | 1,672,687,132 |
se_78804721 | stackoverflow | MACHINE_LEARNING | How to handle zero-padded sequences in 1D CNNs to avoid dependency on padding length? | How to handle zero-padded sequences in 1D CNNs to avoid dependency on padding length?
I am working on a feature prediction task from time series data using the following 1D CNN model:
import torch
import torch.nn as nn
import torch.nn.functional as F
class My1DCNN(nn.Module):
def __init__(self):
super(My1... | https://stackoverflow.com/questions/78804721/how-to-handle-zero-padded-sequences-in-1d-cnns-to-avoid-dependency-on-padding-le | python, deep-learning, pytorch, time-series, conv-neural-network | 1,722,197,276 |
se_66667550 | stackoverflow | MACHINE_LEARNING | training loss is nan in keras LSTM | training loss is nan in keras LSTM
I have tun this code in google colab with GPU to create a multilayer LSTM. It is for time series prediction.
from keras.models import Sequential
from keras.layers import Dense
from keras.layers import LSTM
import tensorflow as tf
from tensorflow.keras.models import Sequential
from te... | https://stackoverflow.com/questions/66667550/training-loss-is-nan-in-keras-lstm | keras, deep-learning, time-series, lstm | 1,615,959,602 |
se_78803752 | stackoverflow | MACHINE_LEARNING | My PyTorch Model in Kaggle uses 100% CPU and 0% GPU During Training | My PyTorch Model in Kaggle uses 100% CPU and 0% GPU During Training
I'm trying to fine-tune a PyTorch classification model to classify plant disease images. I have properly initialized the CUDA device and sent the model, train, validation, and test data to the device. However, when training the model, it uses 100% CPU... | https://stackoverflow.com/questions/78803752/my-pytorch-model-in-kaggle-uses-100-cpu-and-0-gpu-during-training | python, deep-learning, pytorch, gpu, kaggle | 1,722,169,452 |
se_78804096 | stackoverflow | MACHINE_LEARNING | AttributeError: module 'torch' has no attribute 'version' in my imports | AttributeError: module 'torch' has no attribute 'version' in my imports
import torch
import torch.nn as nn
import torch.optim as optim
import torchvision
and getting following error
---------------------------------------------------------------------------
AttributeError Tr... | https://stackoverflow.com/questions/78804096/attributeerror-module-torch-has-no-attribute-version-in-my-imports | python, machine-learning, deep-learning, pytorch, attributeerror | 1,722,179,545 |
se_77273071 | stackoverflow | MACHINE_LEARNING | Guidance with a model that works with grayscale images | Guidance with a model that works with grayscale images
I have a model that consists in 3 conv2D layers, and ReLU activations. It takes as an input grayscale images that are normalised to the interval [0,1]. The input images have some black regions, some white ones, and others in between.
However, the outputs dynamic r... | https://stackoverflow.com/questions/77273071/guidance-with-a-model-that-works-with-grayscale-images | python, deep-learning, pytorch, neural-network, computer-vision | 1,697,027,311 |
se_78799800 | stackoverflow | MACHINE_LEARNING | Why is the gradient wrt input zero? | Why is the gradient wrt input zero?
This snippet tries to take gradient wrt the input to a trained model
import torch
import torch.nn as nn
DATASET_SIZE = 10
TUNING_EPOCH = 10
RANDOMIZATION = "rand"
shape = (10000,)
bsize = 1
device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
input = eval(f"torc... | https://stackoverflow.com/questions/78799800/why-is-the-gradient-wrt-input-zero | python, deep-learning, pytorch | 1,722,025,729 |
se_64968060 | stackoverflow | MACHINE_LEARNING | "Didn't find engine for operation quantized" error while using dynamic quantization with Huggingface transformer | "Didn't find engine for operation quantized" error while using dynamic quantization with Huggingface transformer
I am trying to do dynamic quantization(quantizes the weights and the activations) on a pytorch pre-trained model from huggingface library. I have referred this link and found dynamic quantizat... | https://stackoverflow.com/questions/64968060/didnt-find-engine-for-operation-quantized-error-while-using-dynamic-quantizat | deep-learning, pytorch, quantization | 1,606,132,970 |
se_78800233 | stackoverflow | MACHINE_LEARNING | Figuring out the difference between cv::imread / cv::dnn::blobFromImage and QImage | Figuring out the difference between cv::imread / cv::dnn::blobFromImage and QImage
I have the following image loading code (example: to feed YOLO recognition algorithm) which works:
cv::Mat image = imread(image_path, cv::IMREAD_COLOR);
cv::Mat blob = cv::dnn::blobFromImage(
image,
1 / 255.0,
cv::Size(640, 640),
... | https://stackoverflow.com/questions/78800233/figuring-out-the-difference-between-cvimread-cvdnnblobfromimage-and-qima | c++, qt, opencv, deep-learning, qimage | 1,722,039,371 |
se_66948436 | stackoverflow | MACHINE_LEARNING | ImageNet dataset images not loading properly | ImageNet dataset images not loading properly
I see that we can't download ImageNet dataset from Pytorch directly now. I get this error:
RuntimeError: The dataset is no longer publicly accessible. You need to download the archives externally and place them in the root directory.
So I went on the website and downloaded... | https://stackoverflow.com/questions/66948436/imagenet-dataset-images-not-loading-properly | python-3.x, deep-learning, computer-vision, dataset, imagenet | 1,617,598,882 |
se_78797528 | stackoverflow | MACHINE_LEARNING | Inconsistent Model Predictions When Using Entire Validation Dataset vs. Batch Sampling in TensorFlow | Inconsistent Model Predictions When Using Entire Validation Dataset vs. Batch Sampling in TensorFlow
I am training a deep learning model using TensorFlow and Keras on an image classification task. My model achieves high validation accuracy when evaluated using the validation_ds dataset. However, when I manually sample... | https://stackoverflow.com/questions/78797528/inconsistent-model-predictions-when-using-entire-validation-dataset-vs-batch-sa | python, tensorflow, deep-learning, computer-vision, artificial-intelligence | 1,721,989,786 |
se_76300474 | stackoverflow | MACHINE_LEARNING | mT5 Question/Answering fine tuning is generating empty sentences during inference | mT5 Question/Answering fine tuning is generating empty sentences during inference
mT5-small Question Answering training is converging to high accuracy, high validation accuracy, near-zero low loss; however, when testing the model on trained questions, I am always receiving empty answers.
Experiment Language: Arabic
D... | https://stackoverflow.com/questions/76300474/mt5-question-answering-fine-tuning-is-generating-empty-sentences-during-inferenc | deep-learning, nlp-question-answering, fine-tuning, large-language-model | 1,684,680,564 |
se_63542803 | stackoverflow | MACHINE_LEARNING | No module named 'tensorflow.keras.layers.experimental.preprocessing' | No module named 'tensorflow.keras.layers.experimental.preprocessing'
Below the code
import numpy as np
np.random.seed(0)
from sklearn import datasets
import matplotlib.pyplot as plt
%matplotlib inline
%config InlineBackend.figure_format ='retina'
from keras.models import Sequential
from keras.layers import De... | https://stackoverflow.com/questions/63542803/no-module-named-tensorflow-keras-layers-experimental-preprocessing | tensorflow, machine-learning, keras, deep-learning, neural-network | 1,598,149,109 |
se_78793176 | stackoverflow | MACHINE_LEARNING | Processing Frames instead of jpg images for Deep Learning Model | Processing Frames instead of jpg images for Deep Learning Model
I've been trying to implement live translation with a sign language cnn model i made with Keras and OpenCV and im running into an issue with converting the frames to a format the model is able to predict off of.
imgs_dir = r'C:\Users\danie\sign-language-a... | https://stackoverflow.com/questions/78793176/processing-frames-instead-of-jpg-images-for-deep-learning-model | python, opencv, keras, deep-learning, jupyter-notebook | 1,721,908,841 |
se_72304679 | stackoverflow | MACHINE_LEARNING | What is difference between .h5 and .hdf5 format? | What is difference between .h5 and .hdf5 format?
Suppose we have saved our model as h5 then we can load model using load_model function of keras..
I have gone through multiple github links where the author provides weights file (.h5 or .hdf5 file).
So can we use those pretrained weights/model using load_model?
what is... | https://stackoverflow.com/questions/72304679/what-is-difference-between-h5-and-hdf5-format | python, tensorflow, keras, deep-learning, pre-trained-model | 1,652,963,789 |
se_51329974 | stackoverflow | MACHINE_LEARNING | Accumulating output from a graph using tf.while_loop | Accumulating output from a graph using tf.while_loop
I have an RNN that is stacked on top of a CNN.
The CNN was created and trained separately. To clarify things, let's suppose the CNN takes input in the form of a [BATCH SIZE, H, W, C] placeholder (H = height, W = width, C = number of channels).
Now, when stacked on t... | https://stackoverflow.com/questions/51329974/accumulating-output-from-a-graph-using-tf-while-loop | python, tensorflow, deep-learning, recurrent-neural-network | 1,531,502,052 |
se_78784723 | stackoverflow | MACHINE_LEARNING | Why my RNN does not converge to a simple task? | Why my RNN does not converge to a simple task?
I want to create a recursice model to solve the most simple sequence that I know, Arithmetic progression. With having a as the base and d as the step size, the sequence would be as follows:
a, a+d, a+2d, a+3d, a+4d, ...
To solve this, denoting hidden state as h, the model... | https://stackoverflow.com/questions/78784723/why-my-rnn-does-not-converge-to-a-simple-task | python, machine-learning, deep-learning, pytorch, recurrent-neural-network | 1,721,753,969 |
se_78784562 | stackoverflow | MACHINE_LEARNING | Script for streaming Mistral-7B LLM output only streams on server side. Client gets full output | Script for streaming Mistral-7B LLM output only streams on server side. Client gets full output
I designed a remote server - client pipeline, which is supposed to load the model on the server and stream the output of the model.
At the moment, the output is correctly streamed, but only inside the server, meaning that t... | https://stackoverflow.com/questions/78784562/script-for-streaming-mistral-7b-llm-output-only-streams-on-server-side-client-g | deep-learning, pytorch, large-language-model, mistral-7b | 1,721,751,414 |
se_68088889 | stackoverflow | MACHINE_LEARNING | How to add InstanceNormalization on Tensorflow/keras | How to add InstanceNormalization on Tensorflow/keras
I am new to TensorFlow and Keras, I have been making a dilated resnet and wanted to add instance normalization on a layer but I could not as it keeps throwing errors.
I am using tensorflow 1.15 and keras 2.1. I commented out the BatchNormalization part which works a... | https://stackoverflow.com/questions/68088889/how-to-add-instancenormalization-on-tensorflow-keras | tensorflow, machine-learning, keras, deep-learning, normalization | 1,624,385,645 |
se_64751157 | stackoverflow | MACHINE_LEARNING | How to Use Class Weights with Focal Loss in PyTorch for Imbalanced dataset for MultiClass Classification | How to Use Class Weights with Focal Loss in PyTorch for Imbalanced dataset for MultiClass Classification
I am working on Multiclass Classification (4 classes) for Language Task and I am using the BERT model for classification task. I am following this blog post Transfer Learning for NLP: Fine-Tuning BERT for Text Clas... | https://stackoverflow.com/questions/64751157/how-to-use-class-weights-with-focal-loss-in-pytorch-for-imbalanced-dataset-for-m | python, machine-learning, deep-learning, neural-network, pytorch | 1,604,922,829 |
se_78748344 | stackoverflow | MACHINE_LEARNING | GPT-2 model from hugging face always generate same result | GPT-2 model from hugging face always generate same result
Why were all the results I got from the GPT-2 model the same no matter what I fed into it?
The following are my operating details.
First I download the needed files from the official website. These files included config.json, merges.txt, pytorch_model.bin, toke... | https://stackoverflow.com/questions/78748344/gpt-2-model-from-hugging-face-always-generate-same-result | deep-learning, pytorch, huggingface-transformers, large-language-model, gpt-2 | 1,721,025,119 |
se_76441777 | stackoverflow | MACHINE_LEARNING | huggingface evaluate function use multiple labels | huggingface evaluate function use multiple labels
I have two sentence that combine with encode_plus function and i want to done the NLI task with finetuning a BERT base model.
I want a metric name for huggingface evaluator function to evaluate multiple labels.
i used from this code:
metric = evaluate.combine(["accurac... | https://stackoverflow.com/questions/76441777/huggingface-evaluate-function-use-multiple-labels | python, deep-learning, pytorch, huggingface | 1,686,325,262 |
se_75687534 | stackoverflow | MACHINE_LEARNING | How to balance a PyTorch dataset? | How to balance a PyTorch dataset?
I have an imbalanced PyTorch dataset.
The number of A and V samples is much lower than the others
I would like to ballanase my dataset, even if I have to delete samples that belong to the prevailing class. How can do it?
Now I just remove samples of certain classes if their number exc... | https://stackoverflow.com/questions/75687534/how-to-balance-a-pytorch-dataset | python, deep-learning, pytorch | 1,678,379,854 |
se_78780556 | stackoverflow | MACHINE_LEARNING | TensorFlow - ValueError: Argument `output` must have rank (ndim) `target.ndim - 1` | TensorFlow - ValueError: Argument `output` must have rank (ndim) `target.ndim - 1`
I'm trying to train a sequential model on the TinyImageNet dataset, using TensorFlow.
TinyImageNet has 200 classes, 100k rows for training and 10k for validating. It has two columns, image and label.
The structure of an instance:
{
'i... | https://stackoverflow.com/questions/78780556/tensorflow-valueerror-argument-output-must-have-rank-ndim-target-ndim | python, tensorflow, deep-learning, typeerror, valueerror | 1,721,678,075 |
se_78773489 | stackoverflow | MACHINE_LEARNING | Combine three trained binary classification models into single multiclassification model in keras | Combine three trained binary classification models into single multiclassification model in keras
I have three trained binary classification models, they are trained with sigmoid activation at output layer.
First model returning probability scalar from 0 to 1 to check whether image is number ZERO or not.
Second model... | https://stackoverflow.com/questions/78773489/combine-three-trained-binary-classification-models-into-single-multiclassificati | python, tensorflow, machine-learning, keras, deep-learning | 1,721,497,445 |
se_46941747 | stackoverflow | MACHINE_LEARNING | Tensorflow Error: "Cannot parse tensor from proto" | Tensorflow Error: "Cannot parse tensor from proto"
I am creating a deep CNN with tensorflow. I have already created the architecture, and now I am in the process of training. When I begin to train the model, I use the command:
sess.run(tf.global_variables_initializer())
When this command is called, I get th... | https://stackoverflow.com/questions/46941747/tensorflow-error-cannot-parse-tensor-from-proto | python, tensorflow, deep-learning, conv-neural-network | 1,508,964,288 |
se_77720145 | stackoverflow | MACHINE_LEARNING | pip install deepspeed ERROR: error: subprocess-exited-with-error/error: metadata-generation-failed | pip install deepspeed ERROR: error: subprocess-exited-with-error/error: metadata-generation-failed
When I try to install the deepspeed library in the conda virtual environment, the following error occurs
Collecting deepspeed
Using cached deepspeed-0.12.6.tar.gz (1.2 MB)
Preparing metadata (setup.py) ... error
er... | https://stackoverflow.com/questions/77720145/pip-install-deepspeed-error-error-subprocess-exited-with-error-error-metadata | python, deep-learning, triton, deepspeed | 1,703,653,961 |
se_78766178 | stackoverflow | MACHINE_LEARNING | ValueError: expected sequence of length 129 at dim 1 (got 46) | ValueError: expected sequence of length 129 at dim 1 (got 46)
I was trying to fine-tune an image-to-text model using the following code:
import json
import torch
from torch.utils.data import DataLoader
import io
from transformers import VisionEncoderDecoderModel, AutoTokenizer, AutoFeatureExtractor, Seq2SeqTrainer, Se... | https://stackoverflow.com/questions/78766178/valueerror-expected-sequence-of-length-129-at-dim-1-got-46 | python, machine-learning, deep-learning, huggingface-transformers | 1,721,328,037 |
se_78762914 | stackoverflow | MACHINE_LEARNING | Unable to Import `bm3d` Package in Google Colab After Installation | Unable to Import `bm3d` Package in Google Colab After Installation
I am trying to use the bm3d package for image denoising in Google Colab. I was able to use it without any issues a few days ago. However, now I am facing an import error even though the package installs successfully.
Install the bm3d package:
!pip ins... | https://stackoverflow.com/questions/78762914/unable-to-import-bm3d-package-in-google-colab-after-installation | python, machine-learning, deep-learning, artificial-intelligence | 1,721,286,993 |
se_71998978 | stackoverflow | MACHINE_LEARNING | early stopping in PyTorch | early stopping in PyTorch
I tried to implement an early stopping function to avoid my neural network model overfit. I'm pretty sure that the logic is fine, but for some reason, it doesn't work.
I want that when the validation loss is greater than the training loss over some epochs, the early stopping function returns ... | https://stackoverflow.com/questions/71998978/early-stopping-in-pytorch | python, deep-learning, neural-network, pytorch, early-stopping | 1,650,886,950 |
se_78752899 | stackoverflow | MACHINE_LEARNING | LR not decaying for pytorch AdamW even after hundreds of epochs | LR not decaying for pytorch AdamW even after hundreds of epochs
I have the following code using AdamW optimizer from Pytorch:
optimizer = AdamW(params=self.model.parameters(), lr=0.00005)
I tried to log in using wandb as follows:
lrs = {f'lr_group_{i}': param_group['lr']
for i, param_group in enumerate(self.op... | https://stackoverflow.com/questions/78752899/lr-not-decaying-for-pytorch-adamw-even-after-hundreds-of-epochs | python, machine-learning, deep-learning, pytorch | 1,721,110,184 |
se_78757193 | stackoverflow | MACHINE_LEARNING | How to change shape of multi head self-attention output to a shape that can be fed to convolution layer? | How to change shape of multi head self-attention output to a shape that can be fed to convolution layer?
I encountered an error like this:
The output of MHSA (multi-head self-attention) is as follows:
torch.Size([20, 197, 768])
20 for batch size
197 for sequence length (previously 196, after adding the class token i... | https://stackoverflow.com/questions/78757193/how-to-change-shape-of-multi-head-self-attention-output-to-a-shape-that-can-be-f | python, machine-learning, deep-learning, pytorch, vision-transformer | 1,721,175,846 |
se_78759613 | stackoverflow | MACHINE_LEARNING | AttributeError: module 'keras.src.activations' has no attribute 'get' | AttributeError: module 'keras.src.activations' has no attribute 'get'
I am running the following error when I try to optimize a LSTM using keras tuner in Python: AttributeError: module 'keras.src.activations' has no attribute 'get'.
I am using the following versions: | Python version: 3.11.7 | Keras ve... | https://stackoverflow.com/questions/78759613/attributeerror-module-keras-src-activations-has-no-attribute-get | python, tensorflow, keras, deep-learning | 1,721,220,504 |
se_78680846 | stackoverflow | MACHINE_LEARNING | How to See Evaluation Metrics in YOLOv6? | How to See Evaluation Metrics in YOLOv6?
I have the following output but can't figure out how to evaluate because there is no F1 score or confusion matrix.
Average Recall (AR) @[ IoU=0.50:0.95 | area= small |maxDets=100] = -1.000
Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.250
Average Reca... | https://stackoverflow.com/questions/78680846/how-to-see-evaluation-metrics-in-yolov6 | machine-learning, deep-learning, visualization, yolo | 1,719,554,112 |
se_78228902 | stackoverflow | MACHINE_LEARNING | How can I correct an input_shape error produced when following the "Overfit and underfit" TensorFlow tutorial? | How can I correct an input_shape error produced when following the "Overfit and underfit" TensorFlow tutorial?
I am working through the "Overfit and underfit" TensorFlow tutorial and have reproduced all steps up to the tiny_model using the code they supply. However, when I run the command
size_histories['Ti... | https://stackoverflow.com/questions/78228902/how-can-i-correct-an-input-shape-error-produced-when-following-the-overfit-and | tensorflow, keras, deep-learning, tf.keras | 1,711,502,824 |
se_78707387 | stackoverflow | MACHINE_LEARNING | How to use Pretrained Hugging face all-MiniLM-L6-v2 model as cross encoder using java Deep Java Library | How to use Pretrained Hugging face all-MiniLM-L6-v2 model as cross encoder using java Deep Java Library
I am using deep java library and i want to implement reranking on retrieved documents for my chatbot implementation.
cross encoders are used to find similarity score between 2 strings
Below is the code that generate... | https://stackoverflow.com/questions/78707387/how-to-use-pretrained-hugging-face-all-minilm-l6-v2-model-as-cross-encoder-using | deep-learning, huggingface-transformers, sentence-transformers, djl | 1,720,099,708 |
se_77581428 | stackoverflow | MACHINE_LEARNING | Get values of 'model.fit' keras API parameters | Get values of 'model.fit' keras API parameters
I am trying to get detailed information of the Kera sequential model using a customized callback function. I need to extract all values of the parameters set in model.fit() API such as batch_size, epochs, validation_split, etc. But I could not access them in Keras... | https://stackoverflow.com/questions/77581428/get-values-of-model-fit-keras-api-parameters | python, machine-learning, keras, deep-learning | 1,701,375,225 |
se_78755215 | stackoverflow | MACHINE_LEARNING | Difference between the expected input tensor order for LSTM and Conv1d? | Difference between the expected input tensor order for LSTM and Conv1d?
I am working with time series data and have noticed a discrepancy in the input tensor order required for LSTM and Conv1d/BatchNorm1d/Dropout1d layers in PyTorch. For example, say I have an input tensor that has the shape (Batch Size, Sequence Leng... | https://stackoverflow.com/questions/78755215/difference-between-the-expected-input-tensor-order-for-lstm-and-conv1d | deep-learning, pytorch, time-series, lstm, tensor | 1,721,140,518 |
se_68736617 | stackoverflow | MACHINE_LEARNING | units present for non existing layers in keras tuner results for sequential model | units present for non existing layers in keras tuner results for sequential model
I am using keras tuner for hyperparameter tuning of ANN model. I am changing the no of layers in the model between 2 and 5, and nodes between 10 and 30. I am using random search model of keras tuner to select the best performing models.
... | https://stackoverflow.com/questions/68736617/units-present-for-non-existing-layers-in-keras-tuner-results-for-sequential-mode | python, keras, deep-learning, neural-network, keras-tuner | 1,628,661,039 |
se_78751670 | stackoverflow | MACHINE_LEARNING | Taking derivatives with multiple inputs in JAX | Taking derivatives with multiple inputs in JAX
I am trying to take first and second derivatives of functions in JAX however, my ways of doing that give me the wrong number or zeros. I have an array with two columns for each variable and two rows for each input
import jax.numpy as jnp
import jax
rng = rng = jax.random... | https://stackoverflow.com/questions/78751670/taking-derivatives-with-multiple-inputs-in-jax | python, machine-learning, deep-learning, jax, automatic-differentiation | 1,721,072,868 |
se_78467998 | stackoverflow | MACHINE_LEARNING | Preparation of multivariate time series data | Preparation of multivariate time series data
I am doing a university project on index/stock price prediction. I plan to use a combined cnn-lstm model, and I have several different types of data: Open High Low Close Volume, values, fundamental data such as unemployment and various rates, technical indicators like RSI, ... | https://stackoverflow.com/questions/78467998/preparation-of-multivariate-time-series-data | machine-learning, keras, deep-learning, time-series, forecasting | 1,715,520,010 |
se_78735084 | stackoverflow | MACHINE_LEARNING | Depreciation of some function in python: Ambiguous truth value of dataframe | Depreciation of some function in python: Ambiguous truth value of dataframe
I was training various ANN when I encountered this error in this part. I don't know if any function has been depreciated or not.
def analyze_results(rainfall_data, test_rainfall_data, name, flag=False):
optimized_params = rainfall_data.loc... | https://stackoverflow.com/questions/78735084/depreciation-of-some-function-in-python-ambiguous-truth-value-of-dataframe | python, machine-learning, deep-learning, neural-network, time-series | 1,720,695,134 |
se_75536174 | stackoverflow | MACHINE_LEARNING | How does one create a custom hugging face model that is compatible with the HF trainer? | How does one create a custom hugging face model that is compatible with the HF trainer?
I want to create a new hugging face (HF) architecture with some existing tokenizer (any one that is excellent is fine). Let's say decoder to make it concrete (but both is better).
How does one do this? I found this https://huggingf... | https://stackoverflow.com/questions/75536174/how-does-one-create-a-custom-hugging-face-model-that-is-compatible-with-the-hf-t | deep-learning, pytorch, huggingface-transformers, huggingface-tokenizers, huggingface | 1,677,086,675 |
se_78746376 | stackoverflow | MACHINE_LEARNING | Torch Not Detecting CUDA on NVIDIA Tesla T4 GPU Despite Proper Setup | Torch Not Detecting CUDA on NVIDIA Tesla T4 GPU Despite Proper Setup
I am currently working on a medical image analysis project where GPU acceleration is crucial for performance. Despite enabling the GPU through the green icon in the top right corner of the Lightning.AI interface, Torch indicates that CUDA is not avai... | https://stackoverflow.com/questions/78746376/torch-not-detecting-cuda-on-nvidia-tesla-t4-gpu-despite-proper-setup | deep-learning, pytorch, nvidia, lightning | 1,720,960,212 |
se_65651544 | stackoverflow | MACHINE_LEARNING | NameError: name 'plot_confusion_matrix' is not defined | NameError: name 'plot_confusion_matrix' is not defined
I am trying to make a classification model using VGG16 but at the end of the project I faced an error for getting the Confusion Matrix. Below the codes are given,
Imported packages and modules are:
import os
import keras
import numpy as np
import tensorflo... | https://stackoverflow.com/questions/65651544/nameerror-name-plot-confusion-matrix-is-not-defined | python, machine-learning, deep-learning, classification, vgg-net | 1,610,268,798 |
se_74314961 | stackoverflow | MACHINE_LEARNING | K-Fold cross validation on segmentation task in deep learning | K-Fold cross validation on segmentation task in deep learning
I'm new to deep learning and i wanted to do semantic segmentation task with U-Net, i heared one of the strategies to make my results better is to use cross-validation which is not very popular in deep learning.
I made some reasearch to find out how to imple... | https://stackoverflow.com/questions/74314961/k-fold-cross-validation-on-segmentation-task-in-deep-learning | deep-learning, cross-validation, semantic-segmentation | 1,667,554,965 |
se_77328205 | stackoverflow | MACHINE_LEARNING | How to extract the files of ImageNet-1K dataset for each class separately? | How to extract the files of ImageNet-1K dataset for each class separately?
I have downloaded the ImageNet1K data from https://huggingface.co/datasets/imagenet-1k/tree/main/data . However, the tar files include images with the filenames ILSVRC2012_val_00000009_n03794056.JPEG . Is there any script to contract the files ... | https://stackoverflow.com/questions/77328205/how-to-extract-the-files-of-imagenet-1k-dataset-for-each-class-separately | python-3.x, deep-learning, pytorch, imagenet | 1,697,773,226 |
se_78723204 | stackoverflow | MACHINE_LEARNING | problem on state representaion Finrl StockTradingEnv | problem on state representaion Finrl StockTradingEnv
i'm trying to adjust and apply my own trading strategies on Finrl meta environment and ensmeble agent method. in this process i decide to add some new features which are produced by a neuran network to capture unseen temporal dynamics in the dataset. after applying... | https://stackoverflow.com/questions/78723204/problem-on-state-representaion-finrl-stocktradingenv | deep-learning, reinforcement-learning, trading, algorithmic-trading, finrl | 1,720,482,265 |
se_68461204 | stackoverflow | MACHINE_LEARNING | Continual pre-training vs. Fine-tuning a language model with MLM | Continual pre-training vs. Fine-tuning a language model with MLM
I have some custom data I want to use to further pre-train the BERT model. I’ve tried the two following approaches so far:
Starting with a pre-trained BERT checkpoint and continuing the pre-training with Masked Language Modeling (MLM) + Next Sentence Pr... | https://stackoverflow.com/questions/68461204/continual-pre-training-vs-fine-tuning-a-language-model-with-mlm | deep-learning, nlp, huggingface-transformers, bert-language-model, pre-trained-model | 1,626,814,364 |
se_78712668 | stackoverflow | MACHINE_LEARNING | Loss function not decreasing on a CNN model? | Loss function not decreasing on a CNN model?
I am a creating a CNN model in order to detect emotions (I am very new to creating neural networks). The dataset I used had this structure:
DatasetName ->
train ->
0
1
2
3
4
5
6
7
where each number was a folder of data for a singular emotion. Each image is colored with a va... | https://stackoverflow.com/questions/78712668/loss-function-not-decreasing-on-a-cnn-model | python, machine-learning, deep-learning, pytorch, conv-neural-network | 1,720,200,029 |
se_77409777 | stackoverflow | MACHINE_LEARNING | yolo8 masks detection gives me multiple contours | yolo8 masks detection gives me multiple contours
I edited the question after i experimented a bit more !
I am experimenting with yolo8.
I made a test script to show the problem:
#
# test script to explore multi contours for 1 found object.
import numpy as np
import cv2
img = cv2.imread('demo.jpg')
imgcopy = img.copy... | https://stackoverflow.com/questions/77409777/yolo8-masks-detection-gives-me-multiple-contours | machine-learning, deep-learning, image-segmentation, yolo, semantic-segmentation | 1,698,929,953 |
se_76604196 | stackoverflow | MACHINE_LEARNING | Save the model with the best optuna trial | Save the model with the best optuna trial
I have trained a model using optuna (PyTorch) where number of trials was 5.
This is what my output looks like :
Now, the 4th trial is the best trial. I dont just want the best parameter values, I want to save the model with these values for lr and optimizer. I want to know ho... | https://stackoverflow.com/questions/76604196/save-the-model-with-the-best-optuna-trial | deep-learning, pytorch, hyperparameters, optuna | 1,688,382,792 |
se_61556662 | stackoverflow | MACHINE_LEARNING | Tensorflow Neural Network with more than 2 categories | Tensorflow Neural Network with more than 2 categories
So i watched a tensorflow tutorial on udemy and decided to try for myself, he said if you want more than 2 categories change the activation to "softmax" and units to 4 since i have 4 different categories it could be in (changed from 0:1, to 1:4), everything works i... | https://stackoverflow.com/questions/61556662/tensorflow-neural-network-with-more-than-2-categories | python, tensorflow, machine-learning, deep-learning, neural-network | 1,588,409,283 |
se_78721703 | stackoverflow | MACHINE_LEARNING | How do I define/change the accuracy for a non-classification convolutional neural network? | How do I define/change the accuracy for a non-classification convolutional neural network?
I'm using Keras to make a prediction model. It takes in two time series and outputs a number between 0 and 1. Currently, I am getting very low accuracy as the model is only considered "correct" if it gets the exact number. For e... | https://stackoverflow.com/questions/78721703/how-do-i-define-change-the-accuracy-for-a-non-classification-convolutional-neura | machine-learning, keras, deep-learning, neural-network, conv-neural-network | 1,720,452,244 |
se_53275530 | stackoverflow | MACHINE_LEARNING | Categorize a not trained object as unknown object in machine learning using python | Categorize a not trained object as unknown object in machine learning using python
I'm new in machine learning. Currently I'm working on a fruit/vegetable classification project using deep learning with keras. I was able to train the model. So far, it can detect already trained objects correctly but when I'm providing... | https://stackoverflow.com/questions/53275530/categorize-a-not-trained-object-as-unknown-object-in-machine-learning-using-pyth | python, machine-learning, keras, deep-learning, python-3.6 | 1,542,092,571 |
se_55167006 | stackoverflow | MACHINE_LEARNING | SLURM+Docker: How to kill docker-created processes using SLURMs scancel | SLURM+Docker: How to kill docker-created processes using SLURMs scancel
We have currently setup a GPU computing cluster with SLURM as a resource manager. As this is a cluster for deep-learning, we manage dependencies by using nvidia-docker images to facilitate different frameworks and CUDA versions.
Our typical use ... | https://stackoverflow.com/questions/55167006/slurmdocker-how-to-kill-docker-created-processes-using-slurms-scancel | docker, deep-learning, cluster-computing, slurm, nvidia-docker | 1,552,579,114 |
se_58729151 | stackoverflow | MACHINE_LEARNING | Why is my convolutional model for detecting image rotation predicting the same class for every picture? | Why is my convolutional model for detecting image rotation predicting the same class for every picture?
I want my model to detect the angle (in 360 classes) using self-generated pictures of text.
To get more information to train on, the training set pictures are newly generated every epoch with a new random rotation.
... | https://stackoverflow.com/questions/58729151/why-is-my-convolutional-model-for-detecting-image-rotation-predicting-the-same-c | python, tensorflow, machine-learning, keras, deep-learning | 1,573,039,760 |
se_78719197 | stackoverflow | MACHINE_LEARNING | Why reshape is needed for Sequential models after minmaxscaler class? and how to use? | Why reshape is needed for Sequential models after minmaxscaler class? and how to use?
My recent project is based on 'Stock Prediciton" I'm working on df["Open"] as nd.array.
Trying to understand intuitively how this works and whether my predicted data will be correct or not.
A brief explanation about the coding part, ... | https://stackoverflow.com/questions/78719197/why-reshape-is-needed-for-sequential-models-after-minmaxscaler-class-and-how-to | deep-learning, reshape, numpy-ndarray, sequential, minmax | 1,720,416,012 |
se_78705415 | stackoverflow | MACHINE_LEARNING | How can I get the gradient of a certain number of image out of multiple images with Pytorch? Instead of the gradient with all input images? | How can I get the gradient of a certain number of image out of multiple images with Pytorch? Instead of the gradient with all input images?
After I trained a deep neural network (DNN) that takes 6 images as input, I want to evaluate the performance of the model by adding perturbation to the input images. In this case,... | https://stackoverflow.com/questions/78705415/how-can-i-get-the-gradient-of-a-certain-number-of-image-out-of-multiple-images-w | python, machine-learning, deep-learning, pytorch, gradient | 1,720,075,182 |
se_72716154 | stackoverflow | MACHINE_LEARNING | Why can I use model(x, training =True) when I define my own call function without the argument 'training'? | Why can I use model(x, training =True) when I define my own call function without the argument 'training'?
Notice when I created my model, I defined the call function with argument something = False, when I used the model in function train_step, I put in "something =True, training = True", training is not defi... | https://stackoverflow.com/questions/72716154/why-can-i-use-modelx-training-true-when-i-define-my-own-call-function-withou | python, tensorflow, class, machine-learning, deep-learning | 1,655,903,423 |
se_78704234 | stackoverflow | MACHINE_LEARNING | Does using torch.where to threshold a tensor detach it tensor from the computational graph? | Does using torch.where to threshold a tensor detach it tensor from the computational graph?
I'm writing a custom loss function in PyTorch for multiclass semantic segmentation. One part of this function is thresholding select channels from the tensor, which are indicated with tracker_index.
The last part of the functio... | https://stackoverflow.com/questions/78704234/does-using-torch-where-to-threshold-a-tensor-detach-it-tensor-from-the-computati | python, machine-learning, deep-learning, pytorch, neural-network | 1,720,041,204 |
se_78716156 | stackoverflow | MACHINE_LEARNING | How to access or use PaddleOCR API for handwritten text purposes (this is for my mobile application)? | How to access or use PaddleOCR API for handwritten text purposes (this is for my mobile application)?
I'm a beginner building an Android mobile app which has a feature of detecting handwritten texts. I noticed that one of the good models available and is for free is the PaddleOCR. However, the Github documentation is ... | https://stackoverflow.com/questions/78716156/how-to-access-or-use-paddleocr-api-for-handwritten-text-purposes-this-is-for-my | android, deep-learning, ocr, paddleocr | 1,720,309,700 |
se_75904407 | stackoverflow | MACHINE_LEARNING | Default Grid Size for YOLO v8 | Default Grid Size for YOLO v8
YOLO uses a grid where the centers of the detected objects are allocated. In the initial paper the grid was 7x7
What is the grid size in Yolo v8?
The reason I am asking is because of the anchor-free detection, as it no longer calculates depending on the offset from the anchor boxes, but u... | https://stackoverflow.com/questions/75904407/default-grid-size-for-yolo-v8 | machine-learning, deep-learning, computer-vision, object-detection, yolo | 1,680,326,392 |
se_68240165 | stackoverflow | MACHINE_LEARNING | Detectron2 Mask R-CNN cell segmentation - nothing visible | Detectron2 Mask R-CNN cell segmentation - nothing visible
I'm new to deep learning and trying cell segmentation with Detectron2 Mask R-CNN.
I use the images and mask images from http://celltrackingchallenge.net/2d-datasets/ - Simulated nuclei of HL60 cells - the training dataset. The folder I am using is here
I tried ... | https://stackoverflow.com/questions/68240165/detectron2-mask-r-cnn-cell-segmentation-nothing-visible | deep-learning, computer-vision, object-detection, image-segmentation, detectron | 1,625,348,679 |
se_78601773 | stackoverflow | MACHINE_LEARNING | Link prediction - Building a GNN model for heterogenous graph data in PyG | Link prediction - Building a GNN model for heterogenous graph data in PyG
I’m currently engaged in a project that involves the construction of a Graph Neural Network (GNN) model using PyTorch Geometric. The primary objective of this project is to predict train delays in the French railway network through a multistep p... | https://stackoverflow.com/questions/78601773/link-prediction-building-a-gnn-model-for-heterogenous-graph-data-in-pyg | deep-learning, pytorch-geometric, gnn | 1,718,015,394 |
se_78694546 | stackoverflow | MACHINE_LEARNING | Machine Learning Model on Tensorflow, CUDA, cuDNN not working | Machine Learning Model on Tensorflow, CUDA, cuDNN not working
I am trying to run ResNet152 on Jupyter Notebooks within a Conda Environment. Here's my code:
from tensorflow.keras.applications import ResNet50, ResNet101, ResNet152, InceptionResNetV2, DenseNet121
from tensorflow.keras.models import Model
from tensorflow.... | https://stackoverflow.com/questions/78694546/machine-learning-model-on-tensorflow-cuda-cudnn-not-working | python, tensorflow, keras, deep-learning | 1,719,876,658 |
se_78704210 | stackoverflow | MACHINE_LEARNING | GPU in Neural Net slow | GPU in Neural Net slow
I am trying to run the following code in Colab via GPU:
import torch
import torch.nn as nn
import torch.optim as optim
import pandas as pd
import numpy as np
from sklearn.model_selection import ParameterGrid
from google.colab import files
uploaded = files.upload() # Use this to upload your dat... | https://stackoverflow.com/questions/78704210/gpu-in-neural-net-slow | deep-learning, neural-network, conv-neural-network, gpu | 1,720,040,669 |
se_78703688 | stackoverflow | MACHINE_LEARNING | How to train yolov8 to recognize one additional image | How to train yolov8 to recognize one additional image
So I want to train yolov8 with a dataset containing one annotated image ( using roboflow ) to add the label to the current model so that the yielded trained model will recognize the new image.
First I get the one-image-dataset annotated in roboflow like so:
dataset... | https://stackoverflow.com/questions/78703688/how-to-train-yolov8-to-recognize-one-additional-image | python, machine-learning, deep-learning, yolov8, roboflow | 1,720,030,862 |
se_75217346 | stackoverflow | MACHINE_LEARNING | Pytorch Geometric gives me an 'edge_index' error | Pytorch Geometric gives me an 'edge_index' error
I am trying to use Pytorch Geometric on my own custom Dataset. However I keep getting this error "Please ensure that all indices in 'edge_index' point to valid indices in the interval [0, 13) in your node feature matrix and try again."
I checked that the max of ... | https://stackoverflow.com/questions/75217346/pytorch-geometric-gives-me-an-edge-index-error | deep-learning, pytorch, pytorch-geometric, graph-neural-network | 1,674,533,752 |
se_61505749 | stackoverflow | MACHINE_LEARNING | tensorflow:Can save best model only with val_acc available, skipping | tensorflow:Can save best model only with val_acc available, skipping
I have an issue with tf.callbacks.ModelChekpoint. As you can see in my log file, the warning comes always before the last iteration where the val_acc is calculated. Therefore, Modelcheckpoint never finds the val_acc
Epoch 1/30
1/8 [==>.................. | https://stackoverflow.com/questions/61505749/tensorflowcan-save-best-model-only-with-val-acc-available-skipping | python, tensorflow, machine-learning, keras, deep-learning | 1,588,174,684 |
se_46696576 | stackoverflow | MACHINE_LEARNING | Turing completeness of feed-forward neural networks? | Turing completeness of feed-forward neural networks?
I read that RNN are Turing complete but feed-forward neural networks (FFN) are not. But based on universal approximation theorem, FFN can simulate any functions given enough nodes, and we also know that lambda Church calculus (which is based on stateless functions)... | https://stackoverflow.com/questions/46696576/turing-completeness-of-feed-forward-neural-networks | machine-learning, neural-network, deep-learning, computation-theory | 1,507,752,106 |
se_78703866 | stackoverflow | MACHINE_LEARNING | How do I map the outputs of my Keras CNN to something that I can understand? | How do I map the outputs of my Keras CNN to something that I can understand?
I've been getting into Neural Networks recently and I understand a lot of the basics. As of recent I wrote a CNN with Keras that sorts images of cats and dogs into 37 different breeds. Making the model and getting the data was easy and I have... | https://stackoverflow.com/questions/78703866/how-do-i-map-the-outputs-of-my-keras-cnn-to-something-that-i-can-understand | python, tensorflow, keras, deep-learning, neural-network | 1,720,034,031 |
se_78698316 | stackoverflow | MACHINE_LEARNING | Best practice to train DeepLabV3 with different resolution images in PyTorch | Best practice to train DeepLabV3 with different resolution images in PyTorch
I am trying to train PyTorch's DeepLabV3 on COCO 2017 dataset for semantic segmetation but I am unsure on how to deal with the different resolution images. I know that DeepLab's architecture can process them without any problems, but I can't ... | https://stackoverflow.com/questions/78698316/best-practice-to-train-deeplabv3-with-different-resolution-images-in-pytorch | machine-learning, deep-learning, pytorch, semantic-segmentation, deeplab | 1,719,938,340 |
se_59044351 | stackoverflow | MACHINE_LEARNING | Can dropout increases training data performance? | Can dropout increases training data performance?
I am training a neural network with dropout. It happens that as I decrease dropout from 0.9 to 0.7, the loss (cross-validation error) also decreases for the training data data. I noticed also that accuracy increases as I reduce dropout parameter.
It seems odd to me. Do... | https://stackoverflow.com/questions/59044351/can-dropout-increases-training-data-performance | neural-network, deep-learning, training-data, loss-function, dropout | 1,574,746,354 |
se_78369831 | stackoverflow | MACHINE_LEARNING | I want to minimize predicted_Pel obtained from neural network by using 2 decision variables | I want to minimize predicted_Pel obtained from neural network by using 2 decision variables
I want to minimize predicted_Pel obtained from neural network by using 2 decision variables, the following code is working with one decision variable while it is not working with 2 variables and showing error,
It is my dataset... | https://stackoverflow.com/questions/78369831/i-want-to-minimize-predicted-pel-obtained-from-neural-network-by-using-2-decisio | python, optimization, deep-learning, neural-network, gekko | 1,713,845,120 |
se_78699001 | stackoverflow | MACHINE_LEARNING | input_shape error while converting tensorflow model to tensorflow.js model | input_shape error while converting tensorflow model to tensorflow.js model
I want to use my deep learning CNN algorithm in a web application and I converted my tensorflow model, emotion_model.h5 to a tensorflow.js model using this command in the terminal
tensorflowjs_converter --input_format keras models/emotion_model... | https://stackoverflow.com/questions/78699001/input-shape-error-while-converting-tensorflow-model-to-tensorflow-js-model | tensorflow, deep-learning, conv-neural-network, tensorflow.js | 1,719,949,795 |
se_78694533 | stackoverflow | MACHINE_LEARNING | Using SAM-LSTM-RESNET | Using SAM-LSTM-RESNET
I was using the SAM-LSTM-RESNET package and i had a this shape problem.
It is also happenning with the examples pics that come with the package, so it's very wierd that it does not work as it should. Someone knoes how to fix this without modifying the package's code?
from sam_lstm import SalMap
i... | https://stackoverflow.com/questions/78694533/using-sam-lstm-resnet | python, machine-learning, keras, deep-learning, neural-network | 1,719,876,147 |
se_78696299 | stackoverflow | MACHINE_LEARNING | Issue with training Keras model using ModelCheckpoint in Kaggle notebook (Unexpected result of `train_function` (Empty logs)) | Issue with training Keras model using ModelCheckpoint in Kaggle notebook (Unexpected result of `train_function` (Empty logs))
I'm encountering an issue while trying to train a Keras model in a Kaggle notebook using TensorFlow's ModelCheckpoint callback. Here's my setup and the error I'm facing:
Setup:
I'm building a K... | https://stackoverflow.com/questions/78696299/issue-with-training-keras-model-using-modelcheckpoint-in-kaggle-notebook-unexpe | python, tensorflow, keras, deep-learning | 1,719,914,265 |
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