{"id":22419050,"url":"https://github.com/en10/kerasinception","last_synced_at":"2026-03-12T23:31:04.694Z","repository":{"id":75872148,"uuid":"91891961","full_name":"EN10/KerasInception","owner":"EN10","description":"Google Inception-V3 with 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returned=1 errno=0 peeraddr=140.82.121.5:443 state=error: unexpected eof while reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["image-classification","image-recognition","inception-v3","inceptionv3","keras","keras-tensorflow","tensorflow"],"created_at":"2024-12-05T16:13:59.824Z","updated_at":"2026-03-12T23:31:04.686Z","avatar_url":"https://github.com/EN10.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Inception Keras\n\n#### Image Recognition using Keras and Inception-v3\n\nKeras allows ['easy and fast'](https://keras.io) use of models: [example](https://keras.io/applications/#usage-examples-for-image-classification-models).  \n[Inception-v3](https://www.tensorflow.org/tutorials/image_recognition) is a trained image recognition model for tensorflow with 93.9% Top-5 Accuracy.     \n\n* **[Other Keras Models](https://github.com/EN10/KerasModels)**\n\n![Inception arch](https://github.com/EN10/inception-keras/raw/master/images/Inception-v3.png)\n\nIt was trained on 1.2 million images from [ImageNet](http://image-net.org/challenges/LSVRC/2012/index#introduction) to detect [1000 classes](http://image-net.org/challenges/LSVRC/2012/browse-synsets) (or labels for the images).  \n\n![ImageNet](https://github.com/EN10/inception-keras/raw/master/images/ImageNet.png)\n\nIt took [8 NVIDIA Tesla K40s, 2 weeks](https://research.googleblog.com/2016/03/train-your-own-image-classifier-with.html) to train.\n\n![K40](https://github.com/EN10/inception-keras/raw/master/images/K40.jpg)\n\nThis example was built and tested on c9.io or cs50.io as they provide a free Ubuntu VM (docker container) with 512MB RAM and 2GB Disk.\n\n## Install\n\n    sudo pip install -U pip \n    sudo pip install tensorflow \n    sudo pip install h5py pillow \n\n`sudo pip install -U pip` update pip with tensorflow  \n`... h5py` to load weights  \n`... pillow` to load image  \nas `from tensorflow.python.keras ... import` is used, as `keras` is not installed separately  \n`keras` path correct as of `tensorflow 1.4.1`\n\n## Run\n\n`python predict.py`  \nLine 7: Loads image `'image.jpg'` then runs inference on `InceptionV3`.  \nLine 14: Outputs top 5 predictions and probabilities.   \n\n### Performance\n\n**To disable `\"cpu_feature_guard\"`:**  \n`export TF_CPP_MIN_LOG_LEVEL=2`  \n\nImprove Performance:    \n`TensorFlow binary compiled to use: SSE4.1 SSE4.2 AVX`\n\n* [Precompiled](https://github.com/EN10/TensorFlow-For-Poets#performance)\n* [FloydHub](https://github.com/EN10/FloydHub)\n\n### Tensorflow Imports\n[image](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/contrib/keras/python/keras/preprocessing/image.py)  \n[inception_v3](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/contrib/keras/python/keras/applications/inception_v3.py)  \n[preprocess_input(x)](https://github.com/fchollet/keras/blob/master/keras/applications/imagenet_utils.py)","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fen10%2Fkerasinception","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fen10%2Fkerasinception","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fen10%2Fkerasinception/lists"}