image-recognition

问题 I'm training a VGG-16 model from scratch using a dataset containing 3k images. I use Tensorflow platform and 8 cpus without any gpu. Training rate - 0.01, Weight decay - 0.0005, Momentum - 0.9, Batch size - 64, I've kept training for about three days. But the training accuracy has been unchanged, around 15%-20% after 20 epochs. Could anyone give me some hints to improve the accuracy? 回答1: It seems like I have used too large learning rate. Or weight decay does not work as it promises. After I

问题 I try to recognize two areas in the following image. The area inside the inner and the area between the outer and inner - the border - circle with python openCV. I tried different approaches like: Detecting circles images using opencv hough circles Find and draw contours using opencv python That does not fit very well. Is this even possible with classical image processing or do I need some neuronal networking? Edit: Detecting circles images using opencv hough circles # import the necessary

问题 I am a newbie at opencv and python and am trying to collect keypoints and descriptors of faces within an image. I am using HAAR cascade classifier with frontal face template to look for faces in an image. The HAAR cascade gives me a list of coordinates marking the faces in the image. I want to generate a "mask" at those coordinates so that I can use cv2.surf() to extract keypoints and descriptors within the masked region. I don't know how to create that mask. Try this photo as an example to

问题 I am a newbie at opencv and python and am trying to collect keypoints and descriptors of faces within an image. I am using HAAR cascade classifier with frontal face template to look for faces in an image. The HAAR cascade gives me a list of coordinates marking the faces in the image. I want to generate a "mask" at those coordinates so that I can use cv2.surf() to extract keypoints and descriptors within the masked region. I don't know how to create that mask. Try this photo as an example to

问题 I am a newbie at opencv and python and am trying to collect keypoints and descriptors of faces within an image. I am using HAAR cascade classifier with frontal face template to look for faces in an image. The HAAR cascade gives me a list of coordinates marking the faces in the image. I want to generate a "mask" at those coordinates so that I can use cv2.surf() to extract keypoints and descriptors within the masked region. I don't know how to create that mask. Try this photo as an example to

问题 I'm trying to match a slightly irregular shape to a database of shapes. For example, here the contour I'm trying to match: For more information, this is an outline of an HDMI connector, represented as a contour. It is slightly rough as this was taken with a phone while holding the HDMI. This is my database of connectors: HDMI: DVI: 5PinDIN: DB25: These are a lot clearer as these are contours gathered from connector images from the internet. For what I have tried: cv2.matchShapes() Since these

问题 I'm testing some stuff with Dlib and I selected rectangles around instances of an object I want to recognize, using the compiled tool included in tools/imglab/build/imglab. With this xml file describing a few different views of the object I want to detect I run the train object predictor with a few changes: training_xml_path = os.path.join(faces_folder, "cooldataset.xml") testing_xml_path = os.path.join(faces_folder, "cooldataset.xml") and running in the images directory, makes a detector.svm

问题 In order to make an image with better quality, I had do lots of research on filters. Filters are categorized into low, medium and high. After an analysis of these categories of filters, I conclude that Gaussian low-pass filter is the most suitable for me. And I had researched on how to code it in Android. Finally I found that OpenCV has this function. After a few days of headache, I still can't find any solution since I am new to OpenCV. Does anyone can help me? 回答1: Take a look at this

问题 I am trying to run the following code: import tensorflow from imageai.Prediction.Custom import ModelTraining model_trainer = ModelTraining() model_trainer.setModelTypeAsResNet() model_trainer.setDataDirectory("idenprof") model_trainer.trainModel(num_objects=10, num_experiments=200, enhance_data=True, batch_size=32, show_network_summary=True) But I am getting the following error. It says No module name _pywrap_tensorflow_internal . I tried importing tensorflow as well. But the problem still

问题 I am trying to run the following code: import tensorflow from imageai.Prediction.Custom import ModelTraining model_trainer = ModelTraining() model_trainer.setModelTypeAsResNet() model_trainer.setDataDirectory("idenprof") model_trainer.trainModel(num_objects=10, num_experiments=200, enhance_data=True, batch_size=32, show_network_summary=True) But I am getting the following error. It says No module name _pywrap_tensorflow_internal . I tried importing tensorflow as well. But the problem still