27 votes
Accepted

How to calculate mAP for detection task for the PASCAL VOC Challenge?

To answer your questions: Yes your approach is right Of A, B and C the right answer is B. The explanation is the following: In order to calculate Mean Average Precision (mAP) in the context of ...
Dani Mesejo's user avatar
  • 2,226
18 votes
Accepted

How can you include information not present in an image for neural networks?

Other answers suggest to put an additional channel, I disagree. I think it's a very computationally intensive, time consuming process. Moreover, it forces non-pixel data to be processed by Conv ...
Leevo's user avatar
  • 6,225
15 votes

How to calculate mAP for detection task for the PASCAL VOC Challenge?

There is a nice and detailed explanation with an easy to use code on my Github. Certainly it will help you guys.
Rafael Padilla's user avatar
12 votes

How does deep learning helps in detecting multiple objects in single image?

Although many solutions in production systems still use a sliding window as described below in this answer, the field of computer vision is moving quickly. Recent advances in this field include R-CNN ...
Neil Slater's user avatar
  • 28.9k
10 votes

How does deep learning helps in detecting multiple objects in single image?

I'd want to add @Neil_Slater's answer by sharing my application. In my application, I want to train a model that can automatically load a chess position from a chess book like this: Before I did ...
SmallChess's user avatar
  • 3,540
8 votes
Accepted

Train object detection without annotated data/bounding boxes

Yes, there are models that do this. This link points to one of the first papers I believe. The main idea is called weakly supervised object detection. The paper essentially makes three modifications. ...
Leonard Strnad's user avatar
8 votes
Accepted

What techniques to use for image matching

Hashing is the way to go if you want fast -- constant time -- retrieval of nearest neighbors. Here's a recent example using neural networks to learn a binary hash: Deep Learning of Binary Hash Codes ...
Emre's user avatar
  • 10.5k
6 votes

How does the bounding box regressor work in Fast R-CNN?

A very clear and in-depth explanation is provided by the slow R-CNN paper by Author(Girshick et. al) on page 12: C. Bounding-box regression and I simply paste here for quick reading: Moreover, the ...
Anu's user avatar
  • 328
6 votes

How can you include information not present in an image for neural networks?

Edit: after the edit in the question, 1) does not relate so much anymore, but 2) still does. It depends a bit on the form of the location data. If you have a segmentation mask (i.e. another image ...
matthiaw91's user avatar
  • 1,545
5 votes

How can you include information not present in an image for neural networks?

The simplest thing to try out is to put the information in an extra channel of the image. So if you have RGB channels, you could add a four channel which would simply be the location information you ...
n1k31t4's user avatar
  • 14.9k
4 votes

How does the bounding box regressor work in Fast R-CNN?

The paper cited does not mention linear regression at all. What it does is using a neural network to predict continuous variables, and refers to that as regression. The regression that is defined (...
David Masip's user avatar
  • 6,051
4 votes

How does YOLO algorithm detect objects if the grid size is way smaller than the object in the test image?

Each grid predictor in YOLO should only have a high score that an object is within it, if it detects the centre of the bounding rectangle is inside itself. So a grid point that contains only the wing ...
Neil Slater's user avatar
  • 28.9k
4 votes
Accepted

Does resizing images during training affect the bounding box annotations?

My doubt is whether the resize would now change the position of my object according to annotation? Yes, it will. should i annotate on the resized images(resize them myslef before training?) No, ...
Simon Larsson's user avatar
3 votes

Train object detection without annotated data/bounding boxes

Another approach is "Training object class detectors using only human verification" We propose a new scheme for training object detectors which only requires annotators to verify bounding-boxes ...
FindOutIslamNow's user avatar
3 votes

How does deep learning helps in detecting multiple objects in single image?

The question itself is not quite clear, since you don't state that you have a model that can detect one car per run for an image or you are just asking what tools, algorithms or frameworks to use to ...
chewpakabra's user avatar
2 votes

Generic strategy for object detection

The framework you cope with is semi supervised. You have mostly unlabelled data and you can have some labeled data by manual labelling. Active learning is one method to cope with the situation, by ...
DaL's user avatar
  • 2,633
2 votes

Objects Localization Through CNN

Technically this is possible but most approaches combine localization with some sort of classification so that the network can get better at scoring regions, and also removes the problem of having to ...
Pepe Mandioca's user avatar
2 votes

Grouping similar data/images

Try t-SNE (http://lvdmaaten.github.io/tsne/), it can help you group pictures that have the same properties via dimensionality reduction. You can see an example here http://cs.stanford.edu/people/...
wotter's user avatar
  • 183
2 votes

Pre trained vehicle detection network

You can take a look at the YoloNet which detects Objects based on Pascal VOC 2012 dataset. Here is the link to it : https://github.com/pjreddie/darknet/wiki/YOLO:-Real-Time-Object-Detection You ...
Nischal Hp's user avatar
2 votes

Is there something like class-based object detection? Or class-based selective search?

Object detection models (such as SSD, Faster-RCNN, YOLO, R-FCN) are trained to detect specific classes. If you wish to detect a single class, you could train a custom model on this class.
Hafplo's user avatar
  • 21
2 votes

Object Detection classification

In general, you want to show your model all types of "resistors" it would see in the real world. Is it feasible for you to manually go through your dataset and label each of these images as resistor ...
Andy M's user avatar
  • 400
2 votes

Tensorflow Object Detection API

To build a model to detect the old categories and your new ones, you need to re-train the model with your own dataset and the dataset used to pre-train the model. Fortunately, this dataset is ...
Louis Plt's user avatar
2 votes

Similar objects same labels

If you only need to predict whether an object is a pepper or not why bother predicting whether it is a red pepper or a green pepper, you are making your problem more complicated than it needs to be. ...
Robin Nicole's user avatar
2 votes

optical chemical structure recognition from images

What way I could follow to achieve this? Create a dataset with image-label pairs. Create a classification model. I don't think ...
Bruno Lubascher's user avatar
2 votes

How can you include information not present in an image for neural networks?

In the specific case of knowing the location of the object in the image, one technique would be to crop and pad each training example so that the object is in the exact center. This way the extra ...
QuadmasterXLII's user avatar
1 vote

Why is a general/original softmax loss not preferred in FR (face recognition)?

Disadvantage of softmax loss is written in Your referenced paper. "ArcFace" (arxiv.org/pdf/1801.07698.pdf) and "Face recognition via centralized coordinate learning" https://arxiv....
Mason Ji Ming's user avatar
1 vote

How to generate Anchor boxes for SSD?

The source code appears clear: this_steps specifies whether the distance between the anchors is set by the caller or calculated in a straightforward way within the ...
ssegvic's user avatar
  • 111
1 vote

mean average precision - pseudo code

Firstly for your question 2. The precision and recall is calculated across all images, for a single class. Not on a per-image basis and averaging across images. The "A" in "mAP" means averaging across ...
user12075's user avatar
  • 2,264
1 vote

Bounding Boxes in YOLO Model

Andrew Ng's explanation actually covers the YOLOv2 which uses anchor boxes. YOLOv1, which is the paper you linked, does not use anchor boxes so its not exactly the same. They key to understanding how ...
Baymax Lim's user avatar
1 vote
Accepted

In CNN (Convolutional Neural Network), does the combination of previous layer's filters make next layer's filters?

I guess you are making mistake about the filters. After applying filters to the input of each layer, the output will be used as the input of the next layer. The first layer's filters try to find the ...
Green Falcon's user avatar
  • 14.1k

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