Questions tagged [inception]

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Tensorflow SSD inception

Hi there I am new to tensorflow and I am just wondering how long does it usually take for my inception v2 model to recognise 50 objects in a picture. I usually leave my model run for 2000 steps and ...
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CNNs: understanding feature visualization Channel Objectives (SOLVED)

I'm trying to follow a paper on deep NN feature visualization using beautiful examples from the GoogLeNet/Inception CNN. see: https://distill.pub/2017/feature-visualization/ The authors use ...
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278 views

How to compute Frechet Inception Score for MNIST GAN?

I'm starting out with GANs and I am training a DC-GAN on MNIST dataset. The two metrics that are used to evaluate GANs are Inception Score (IS) and Frechet Inception Distance (FID). Since Inception ...
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Confusion regarding prediction results of SVM and ANN on feature vectors

I am making a custom image classifier using Transfer Learning on Inception V3. I have 3 classes of images with ~6K images each. The input dimension of the network is 500X500 and the output of the ...
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Reference for Inception-v2

The "Rethinking" paper doesn't describe the actual implementation of the Inception-v3 model in Tensorflow: an accurate description is written in model.txt in the source files of the paper in the arXiv....
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Very Fast Training After First Epoch

I trained an InceptionV3 model using plant images. I used Keras library. When training was started, first epoch took 29s per step and then other steps took approximately 530ms per step. So that made ...
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Finetuning pretrained inception_v3 in pytorch

I'm following this tutorial but I'm having some trouble with inception. Every architecture works successfully, but when I run the tutorial code for inception, I get the following error: ...
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181 views

How to calculate receptive field size for -ception model?

I have a full convolution model like this: ...
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1answer
561 views

Retrain image classifier using MobileNet v2

I am using my own dataset to retrain mobilenet_v2_100_224 model, I currently have 4 classes where each class have more than 100 images still I'm observing overfitting even though I've used ...
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92 views

Why is the GoogLeNet retrained model size less compared to others?

I have some questions if someone can answer me or guide me articles to understand them. I investigated different pre-trained model i.e. AlexNet, VGG, GoogLeNet, InceptionV3 and ResNet. I have ...
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1answer
69 views

Image features (produced by VGG19) do not properly train an ANN in Keras

I've used a VGG16 network to extract features from an image dataset, creating a features dataset using the following code: ...
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1answer
677 views

Which is the fastest image pretrained model?

I had been working with pre-trained models and was just curious to know the fastest forward propagating model of all the computer vision pre-trained models. I have been trying to achieve faster ...
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1answer
823 views

how to visualize InceptionV3 hidden layers

I am following google codelab: Tensorflow for poet to train my custom model. This google codelab use the Inception-V3 model for training. The inception-V3 model have 48 layer. My question is that ...
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1answer
2k views

difference in between CNN and Inception v3

What is the difference in between the inception v3 and Convolutional neural network?
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Training Inception V3 based model using Keras with Tensorflow Backend

I am currently training a few custom models that require about 12Gb GPU memory at the most. My setup has about 96Gb of GPU memory and python/Jupyter still manages to hog up all the gpu memory to the ...
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317 views

What are towers in inception architecture and tensorflow?

My understanding of towers in inception architecture and in tensorflow terminology is that they are part of a neural network model for which separate computation can happen on forward phase and ...
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435 views

Pretrained InceptionV3 - very low accuracy on Tobacco dataset

I'm trying to fine-tune a pre-trained InceptionV3 on the tobacco-3482 document dataset (I'm only using the first 6 classes), but I'm getting accuracies under 20% on the validation set (> 90% accuracy ...
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2answers
12k views

Where to find list of Tensorflow pretrained models available in download.tensorflow.org/models

I am trying the find the pretrained models (graph.pd and labels.txt) files for Tensorflow (for all of the Inception versions and MobileNet) After much searching I found some models in, https://...
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1answer
737 views

Running Tensorflow MobileNet from Java

I am trying to run Tensorflow for image recognition (classification) in Java (JSE not Android). I am using the code from here, and here. It works for Inceptionv3 models, and for models retrained ...
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652 views

python.framework.errors_impl.permissiondeniederror

I am trying to retrain inception final layer on new set of images. I am using docker TensorFlow image on Windows environment. Below are the steps that I am following. Install docker toolbox for ...
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1answer
726 views

Transfer learning (on pre-trained inception net model) for multi label classification is giving similar probability for all labels

Number of labels: 1000, Dataset size: 200000 images Final probability for 1000 labels is in the range of 0.3 to 0.34. I was expecting large variation in probabilities. Can someone tell me what I am ...
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1answer
91 views

Some questions about GoogleNet paper

This phrase is from the "Rethinking the Inception Architecture for Computer Vision" paper. it says : Higher dimensional representations are easier to process locally within a network. ...
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1answer
1k views

Transfer learning within Tensorflow's inception model

I want to freeze the layers, except the first three layers, in the Inception v3 model with TensorFlow in Python 3, and modify the weights of these three layers to be able to re-initialize and re-train ...
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2answers
324 views

How does inception decrease the computational cost?

From the second paragraph of 3.1 Factorization into smaller convolution in the paper Rethinking the inception architecture for computer vision: This setup clearly reduces the parameter count by ...
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109 views

What is the reason behind the minimum image size in the Keras InceptionResNetV2 model?

In Keras' documentation for the InceptionResNetV2 model, it says the following: input_shape: (...). It should have exactly 3 inputs channels, and width and height should be no smaller than 139. I'...
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114 views

TensorFlow Inception V3

What are bottleneck values and how are they generated? How does the next-to-last layer of Inception use these bottlenecks to generate the accuracy? How is the final accuracy calculated?
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1answer
285 views

Inception/ResNet doing worse than SIFT in feature extraction

We are doing our Thesis on multimodal retrieval. it's basically searching different modalities (multimedia ex: text, video, images ...) with other modalities. i.e. searching a database of images with ...
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1answer
5k views

Tensorflow and OpenCV real-time classification

I am testing the machine learning waters and used TS inception model to retrain the network to classify my desired objects. Initially, my predictions were run on locally stored images and I realized ...
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1answer
881 views

Retraining last layer of inception

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1answer
342 views

Transfer learning inceptionv3

Why is training classifier on extracted features (from inceptionV3) is so much faster than simply stack classifier on topless inception model? From my experience extracting features + training ...
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1answer
905 views

Understanding Imagenet training

I am trying to start training Imagenet classification training using Tensorflow's inception model. I am a bit confused as I am not sure how to fully train the model. Wherever I go everyone seems to ...
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2answers
8k views

Fine-tuning a model from an existing checkpoint with TensorFlow-Slim

I'm trying to retrain the final layer of a pretrained model with a new image dataset using TensorFlow-Slim. Lets say I want to fine-tuning inception-v3 on flowers dataset. Inception_v3 was trained ...
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1answer
309 views

Retrain final layer of Inception model

I'm trying to retrain Inception model final layer for a binary classification. My training image set contain 2000 images in class 1 and more than 6000 images in class 2. Will this huge difference in ...
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117 views

Inception V3 Running Stats?

Has anyone created statistics on how fast and accurate Inception V3 can classify an image based on criteria such as: different models of GPUs/CPUs, input image size, input image ratio, file format, ...
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1answer
52 views

Using TensorFlow's preexistent Inception labeler

I know I can retrain Inception to label images, but can I just provide an image to a non retrained Inception and get a label back?
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1answer
195 views

How to use InceptionV3 without retraining

I know I can retrain Inception to label images, but can I just provide an image to an untrained Inception and get a label back? Is there an API for this? If there is, then why does Google open source ...
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24k views

What is the difference between Inception v2 and Inception v3?

The paper Going deeper with convolutions describes GoogleNet which contains the original inception modules: The change to inception v2 was that they replaced the 5x5 convolutions by two successive ...
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1answer
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What is an inception layer?

I'am reading an article called "FaceNet: A Unified Embedding for Face Recognition and Clustering". And there, they use something called "inception". I guess it's something about layers, but I can't ...