keras image classification

Atitit Classification of mixed folders based on image images and documentsdocuments that are too small ( txt doc csv exl ppt pptx ) Separate categories Mov10kminidocBut there may be some calligraphy pictures migrated because they are tiny and need to be listed separatelytoo small a junk file all migrations below 10kb, not in document format: In addition,JS, CSS, GIF format are all migrated. /atiplatf_cms/sr

References: Learning globally-consistent local Distance Functions for shape-based image retrieval and classification, Andrea frome etc. I fell asleep after summing up last night. Today, I don't know why I owe my hand to the waste basket. I also emptied my upper body of the obsessive-compulsive disorder. Ah, I finally wrote it back, and I was so stupid that I cried. = [Paper] learning globally-consistent

There is more than one label for a picture in the Multi-label Image classification (Multi-label image classification) task, so the evaluation cannot be categorized by the standard single-label image, which is mean accuracy, which uses a similar approach to information retri

Small task: Achieve picture classification1. Picture materialPython bulk compress jpg images: PiL library resizehttp://blog.csdn.net/u012234115/article/details/502484092. Environment ConstructionInstallation version of Python under Windows comparison 2.7 vs 3.6Https://pypi.python.org/pypiInstallation of the PIL Library under WindowsHttps://pypi.python.org/pypiInstallation of the PIL Library under Windowshttp://zjfsharp.iteye.com/blog/2311523Installation and upgrade of PIP under Windowshttp://blo

Source Address: http://blog.chinaunix.net/uid-26020768-id-3155898.html 1. Digital Image Processing, Gonzalez, Ma qiuqi, e-Industry Press; 2. opencv basics, Yu Shiqi, Liu Rui, Beijing University of Aeronautics and Astronautics Press; 3. Learning opencv computer vision with the opencv library, Gary bradski, Adrian kaebler, O 'Reilly 4. pattern recognition, Bian zhaoqi, Zhang xuesong, Tsinghua University Press; 5. Pattern

[ This article refers to the blog: http://blog.csdn.net/orangehdc/article/details/37763933;http://my.oschina.net/Ldpe2G/blog/275922;http:// blog.csdn.net/sheng_ai/article/details/39971599 ] References: [1] Tsung-han Chan, Kui Jia, Shenghua Gao, Jiwen Lu, Zinan Zeng, and Yi Ma, pcanet:a simple Deep Learning-Baseline F or Image classification? 2014 Thesis Link: http://arxiv.org/abs/1404.3606 MATLAB code: MATL

the InceptionV3 and InceptionResNetV2 two models, first saving the two models and then finding the set of the tags predicted by the two models.Some of the code is as follows:def arr2tag (arr1, arr2): Tags= [] forIinchRange (arr1.shape[0]): Tag=[] index1= NP.where(Arr1[i] >0.3) Index2= NP.where(Arr2[i] >0.3) index1= index1[0].tolist () index2= index2[0].tolist () index= List (Set(INDEX1). Union (Set(INDEX2))) Tag= [Hash_tag[j] forJinchindex] tags.append (TAG)returnTagsModel = Load_model ('mo

1. Study the necessity of Noise Characteristics This article mainly introduces the classification and features of common noises. Model the noise, and then use the model to implement all kinds of noise. The aging of various photos in real life can be attributed to the following aging models. This model is very simple and can be expressed directly using the following formula. In the frequency domain, it is expressed in the following formula. Accordin

Android app source code is an Android file browser that can be viewed by music, video, and image classification, This project is an android file browser that supports browsing by music, pictures, and video categories. With multiple options, open, copy, paste, delete, rename, view attributes, and other functions, you can also switch the list display effect and browse the file categories. Unfortunately, ther

test_interval: 4000 #迭代多少次测试一次 test_initialization:false display:40 average_loss:40 base_lr:0.01 lr_policy : "Step" stepsize:320000 #迭代多少次改变一次学习率 gamma:0.96 max_iter:10000000 #迭代次数 momentum:0.9 weight_decay:0.0002 snapshot:40000 snapshot_prefix: "Examples/imagenet/bvlc_googlenet" # The generated Caffemodel is saved under Imagenet, as Bvlc_googlenet_iter_***.caffemodel Solver_mode:gpu At this point, we go back to caffe-master\examples\imagenet, open train_caffenet.sh, modify: (in the case of