image-recognition

问题 Closed. This question is off-topic. It is not currently accepting answers. Want to improve this question? Update the question so it's on-topic for Stack Overflow. Closed 4 years ago . Does anyone know of recent academic work which has been done on logo recognition in images? Please answer only if you are familiar with this specific subject (I can search Google for "logo recognition" myself, thank you very much). Anyone who is knowledgeable in computer vision and has done work on object

问题 Given two different image files (in whatever format I choose), I need to write a program to predict the chance if one being the illegal copy of another. The author of the copy may do stuff like rotating, making negative, or adding trivial details (as well as changing the dimension of the image). Do you know any algorithm to do this kind of job? 回答1: These are simply ideas I've had thinking about the problem, never tried it but I like thinking about problems like this! Before you begin

问题 Closed . This question needs to be more focused. It is not currently accepting answers. Want to improve this question? Update the question so it focuses on one problem only by editing this post. Closed 3 years ago . I have an idea, that is, I want to identify the letters in an image which may be .bmp or .jpg. For example, here is an .bmp image with a letter 'S' in it. What I want to do is to identify the letter using Python. It's kinda similar with those Questions about auth code recognition

问题 I want to implement color detection in Android. What I exactly want to do is that after taking a picture with Android Camera, I want to detect the color of object in that picture. My goal is detecting colors according to color intensity. At this point, I searched and saw different approaches related to this goal. There are some algorithms which converts the images into Bitmap and then detects the colors, some of them use RGB. Additionally, I saw that OpenCV is also a known solution for this

问题 I'm running a HaarTraining process using OpenCV 2.2 (compiled with OpenMP). The training progress shows: +----+----+-+---------+---------+---------+---------+ |7468| 44%|-|-2.712450| 1.000000| 0.719459| 0.108393| +----+----+-+---------+---------+---------+---------+ |7469| 44%|-|-2.712449| 1.000000| 0.719459| 0.108393| +----+----+-+---------+---------+---------+---------+ ....... What does the number 7469 mean (I only have 7000 samples)? How can I know when the process is going to finish?

问题 I am building a basic image recognition app in Swift using the Inception v3 Machine Learning model. I dragged and dropped the Inceptionv3.mlmodel inside my project folder and made sure the "Copy items if needed" option was ticked. Inside the detect function: func detect(image: CIImage) { guard let model = try? VNCoreMLModel(for: Inceptionv3().model) else { fatalError("Loading CoreML Model Failed!") } let request = VNCoreMLRequest(model: model) { (request, error) in guard let results = request

问题 I am trying to code a face-recognition program in Python (I am going to apply k-nn algorithm to classify). First of all, I converted the images into greyscale and then I created a long column vector (by using Opencv's imagedata function) with the image's pixels (128x128= 16384 features total) So I got a dataset like the following (last column is the class label and I only showed first 7 features of the dataset instead of 16384). 176, 176, 175, 175, 177, 173, 178, 1 162, 161, 167, 162, 167,

问题 I'm looking to do some image classification on PDF documents that I convert to images. I'm using tensorflow inception v3 pre trained model and trying to retrain the last layer with my own categories following the tensorflow tuto. I have ~1000 training images per category and only 4 categories. With 200k iterations I can reach up to 90% of successful classifications, which is not bad but still need some work: The issue here is this pre-trained model takes only 300*300p images for input.

问题 i'm trying to recognize munchkin cards from the card game. i've been trying to use a variety of image recognition APIs(google vision api, vize.ai, azure's computer vision api and more), but none of them seem to work ok. they're able to recognize one of the cards when only one appears in the demo image, but when both appear with another one it fails to identify one or the other. i've trained the APIs with a set of about 40 different images per card, with different angles, backgrounds and

问题 I am trying to stop a possible block in my bot program by using PyAutoGUI's Image Recognition function ( pyautogui.locateCenterOnScreen ) to recognize a simple 'OK' button, in order to get rid of the possible block error message. However, the function only sometimes works as I have found out by screenshotting different error messages and comparing the pixel color side by side. The result I have found out is that the pixel color on two different 'OK' buttons are usually off by 1, explaining