Questions tagged [faster-rcnn]

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masked image and language modelling

I was coding this piece of code which heavily relies on the demo of visual question answering, and I'm masking inputs while feeding it to the bert using [MASK] token, and providing a label which ...
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Can I use pre-trained coco weights for medical lesion segmentation? Or should I train the network from scratch?

I am trying to understand in what cases I can benefit from pre-trained weights. Sometimes, pre-trained weights works (can be fine-tuned) for other domains but I cannot understand how to make a ...
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When using a model like VGG16 as a classifier within Faster RCNN, does Faster RCNN then use 2 CNNs in total?

Im currently doing a project about CNN's but im quite confused because they can be used to classify and to extract features. According to the Faster RCNN paper, it uses a ResNet backbone. I have also ...
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Difference between RRPN and R2CNN

I have been working on rotated object detection with Faster R-CNN on aerial imagery for some time and encountered with two different approaches for producing rotated bounding boxes. The first approach ...
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How many model parameters do R-CNN, Fast R-CNN and Faster R-CNN have respectively?

I am making research on object detection and I would like to know the number of parameters these three models obtain.
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Custom Class Using PyTorch Faster-RCNN Model not working

I have been trying the pre-trained faster-rcnn resnet50 PyTorch model in my project, and when I define my function get_detection() as seen below within the same file as where I'm calling it, it works ...
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Object Detection: Unusual warning while training Detectron2 Faster R-CNN

I am trying to train a Detectron2 faster_rcnn_R_50_FPN_3x model on a custom dataset, pretrained on PublayNet Dataset. While training, I am getting the following warning: ...
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How to arrange ground-truth for anchor box representation in object detection

I am working on CharGrid and BERTGrid papers and have questions about bounding box regression decoder part. In the CharGrid paper, it states that there are two outputs from this branch: one with ...
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Feature Map setup for Faster RCNN with resnet50 backbone

I'm trying to get an activation map using a Faster RCNN Resnet50 backbone, but am having issues getting the proper hook setup for output information. Most of the libraries, like gradcam, don't seem to ...
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Which model is used for document extraction (CamScanner, Microsoft Lens etc)

I want to start a small project where I'd create a model(s) that would extract document from a picture and rescale it, something like CamScanner or Microsoft Lens apps do. I've gathered a small ...
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Is it possible to pass in an empty annotation to signify just a background/negative image for faster RCNN?

I'm using a pretrained resnet50 for faster RCNN to detect areas with 2 classes (background and interest class). As part of my data inputs for training, I have background images without any annotation ...
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302 views

How to convert horizontal bounding box coordinates to oriented bounding box coordinates

I am trying to detect oriented bounding boxes with faster rcnn for a long time, but I could not make it to do so. I aim to detect objects in the DOTA dataset. I was using built-in faster rcnn model in ...
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How to get the Feature visualization for pre-trained resnet50 models?

I'm trying to visualize some of the features from a pre-trained resnet50 FasterRCNN. The model downloaded is from torchvision: ...
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What kinds of changes can I attempt on my object detector .config file to improve the detection accuracy?

I have trained an object detection model with 2 classes, around 7500 images, and approx. 10,000 annotations per class. I was able to fine-tune Faster R-CNN with ResNet (V1) from the Tensorflow Object ...
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What does the Region Proposal Network output in Faster-RCNNs?

Does it output corrections and offsets to the anchor boxes(that were generated by using some specific aspect ratios and scales)? Also if this the answer is YES, Suppose I have 3 scales - [8,16,32] and ...
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Compute IoU for each class in Mask R-cnn

I'm trying to compute the IoU, with the matterport Mask R-cnn implementation, for each class (13 in total) that i have in my dataset. For now i managed to compute the average IoU for all the classes ...
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Does Fast-R-CNN model take into account the context?

Does Fast-R-CNN model take into account the local context and global context of objects in an image ? If it doesn't, is there any other models that does that and which is efficient in small object ...
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Understanding how anchors are created in a regional proposal network

I understand that in Faster R-CNN, the image is fed into a pre-trained CNN (such as VG16). So say I have a 37x50x512 feature map. Firstly, I assume that each feature map (37x50x1) is fed into the RPN? ...
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Best way to train yolov5 on a custom dataset

I have a dataset with about 100 images that look like this. My goal is get yolov5 to detect buildings in similar images. In order to do this I would like yolov5 to get to close to 1 in precision on ...
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Count repeating "objects" in a picture

This is my first data-science project and I would love to get some guidance to know how to get started. My problem is the following: I want to count objects that are in a picture. This picture has a ...
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What is the difference between a bounding box and ROI (Region of Interest)

I was reading about the Fast RCNN for object detection. From what I understand, it uses pre-computed ROI's (using selective search) and uses these to predict the bounding box offsets and uses smooth ...
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How to interpret fast-rcnn metrics?

I'm following this tutorial to fine tune Faster RCNN model, during training process a lot of statistics are produced however I don't know how to interpret them. what are major characteristics to look ...
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Faster RCNN is not able to recognize composed elements

I tried to fine tune Faster RCNN to realize object detection task with bounding boxes where I shall recognize face, eyes and mouth on image. However Faster RCNN seems to fail to recognize objects when ...
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Region Proposal Network - How to subsampling 256 fg/bg anchors

I am trying to understand training process of RPN. I have problem with creating mini batches of 256 anchors. If features map has shape 18x25=450 and every position has 9 anchors it is 4050 potential ...
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Preprocess problem Faster RCNN in tensorflow object detection API

I've wrapped meta-architecture with the code below: ...
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2 answers
116 views

Training Object Detection model on just 10 images

I am trying to train an object detection model using Mask-RCNN with Resnet50 as backbone. I am using the pre-trained models from PyTorch's Torchvision library. I have only 10 images that I can use to ...
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Why does Faster R-CNN use SGD optimizer instead of Adam?

I just start learning Faster R-CNN and I have some doubts about the optimizer of this network. In my understanding, Adam optimizer performs much better than SGD in a lot of networks. However, the ...
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Faster RCNN-RPN NETWORK

I already asked this question in stack overflow, but got response from experts, to post this question here, please help me to understand this concept... I am trying to understand RPN network in Faster ...
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How can I calculate the F1 score using Mask RCNN?

I customized the "https://github.com/matterport/Mask_RCNN.git" repository to train with my own data set, for object detection, ignoring the mask segmentation part. Now I am evaluating my results, I ...
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Detect the presence/absense of simple components from a circuit board using object detection

In this case I have a challenge of inspecting a recently mounted product, using computer vision, to detect the absence of any component that I have to check. For this task, I tried the concept of ...
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How to create a feature vector given final set of feature maps?

I've got a faster-rcnn (resnet-101 backbone) for object detection, and am extracting feature tensors for each detected object, which is a 7x7x2048 tensor (basically 2048 feature maps, each 7x7). For ...
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Efficient implementation of seperable convolution in tensorflow

It seems like the native implementation of separable convolution in tensorflow is not efficient. https://github.com/tensorflow/tensorflow/issues/12940 Is anyone aware how can we get an efficient ...
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How many augmentated data points for each training image?

What are some useful rules of thumb for picking the number of augmenters per training image? I realize this is a hyperparameter I can vary and test: I'm just trying to get a sense for reasonable ...
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Image masking tool to implement mask RCNN using python

I am trying to understand Mask RCNN. For that I have to input image with mask in png format while building the model. I try to follow the article present in this blog. The blogger used Pixel ...
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1 vote
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How does a Faster R-CNN gets trained and how does the Region Proposal Network fits into that?

so a Faster R-CNN consists of 3 parts: -the Base CNN -the Region Proposal Network with RoIpooling -and the classification CNN at the end So I asked myself if all these three Networks are trained ...
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2 answers
1k views

Pre trained dataset for Car damage detection

I'm making a Car Damage Detection model which would have 2 classes to detect upon. My dataset has a total of 300 images (out of which I'd be using some for testing), which are totally insufficient to ...
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2 votes
1 answer
381 views

How does R-CNN and AlexNet compare?

I know AlexNet does object classification in images [categories] and R-CNN does object localization [category and bounding box]. How does R-CNN and AlexNet compare? Are they used for the same purpose ...
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Saving images in a non-retraceable way, but still able to train R-CNN's on them

For a computer vision project I am working with images that the company only allows me to have on my computer for a maximum of 24 hours due to regulations. Every day a few hundred images come in via ...
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Object detection model using images which have single instance of class per image-can it detect multiple instances in a single image?

I tried to train Faster R-CNN to detect multiple instances of a single class (eg. pomegranate on a pomegranate tree) but the training data consisted of 200 images where each image had only one object ...
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1 answer
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Extract segment from document scan

I need to extract some "valuable" information from document scan. For example, document's number, incoming date, organizations, persons, etc. Example document: I'm trying to extract highlighted ...
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9 votes
2 answers
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Is Faster RCNN the same thing as VGG-16, RESNET-50, etc... or not?

My understanding is that Faster RCNN is an architecture for performing object detection. It finds objects in an image and classifies them. My understanding is also that VGG-16, RESNET-50, etc... also ...
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1 vote
1 answer
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Tensorflow F-RCNN first stage input and output strides

Trying to optimize performances on Tensorflow's faster_rcnn_resnet50 (from the model zoo), I'm currently working on understanding the full .config file they provide, and I'm having a hard time with ...
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matterport mask-r-cnn transfer learning on own dataset using VGG annotator ver.1

The code I used was taken from shapes.py, balloon.py, inspect_balloon_data.ipynb but mostly ...
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5 votes
2 answers
658 views

Feeding 3 consecutive video frames to a CNN to track a tennis ball

I want to use CNN transfer learning to track a tennis ball from TV broadcasts of tennis matches. I used VGG annotating tool annotation tool link (use version 1 of the tool for compatibility with ...
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1 vote
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Understanding Faster R-CNN

I'm having some trouble understanding the way the Faster R-CNN algorithm works. Specifically, the way the authors describe the concept of anchors. In their paper from here they describe anchors in ...
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3 votes
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Bounding box regression in R-CNN

In R-CNN paper, they give the definition of the target values for bounding box regression Given that $(P, G)$ is a (prediction box, ground-truth box) pair of the form $(x, y, w, h)$ where $x, y$ is ...
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Building Image Dataset In a Studio

I'm currently working in a problem of Object Detection, more specifically we want to count and differentiate similar species of moths. We are already testing some ...
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2 answers
337 views

Can I load my own weights?

Full code source: ...
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2 votes
1 answer
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what is the best approach to detect small objects with similar shape?

I'm working a model which detect different products in supermarket shelf. In the training data, there are a lot of objects with similar shape placed very close to or stacked to each others.(eg: milks ...
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1 vote
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Mask RCNN detecting object but mask is inaccurate

I am trying to detect the inner region of a object. Currently I am using the mask rcnn implementation provided by tensorflow in the models zoo. The object is similar to a hula hoop that is square in ...
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