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https://github.com/policratus/sparkmage
🐘 A tool for blazing fast analysis and clustering of similar images using 🐘 Hadoop and ⚡ Spark.
https://github.com/policratus/sparkmage
big-data computer-vision hadoop image-processing spark
Last synced: about 2 months ago
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🐘 A tool for blazing fast analysis and clustering of similar images using 🐘 Hadoop and ⚡ Spark.
- Host: GitHub
- URL: https://github.com/policratus/sparkmage
- Owner: policratus
- License: gpl-3.0
- Archived: true
- Created: 2017-03-23T20:34:25.000Z (over 7 years ago)
- Default Branch: master
- Last Pushed: 2017-07-13T14:04:07.000Z (about 7 years ago)
- Last Synced: 2024-06-08T23:34:29.268Z (4 months ago)
- Topics: big-data, computer-vision, hadoop, image-processing, spark
- Language: Python
- Homepage:
- Size: 186 KB
- Stars: 2
- Watchers: 3
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
- awesome-blazingly-fast - sparkmage - 🐘 A tool for blazing fast analysis and clustering of similar images using 🐘 Hadoop and ⚡ Spark. (Python)
README
# 👁✨ sparkmage
## 🛠 Installation
Assuming that you've a Unix like OS or emulation, [git](https://git-scm.com/), [Python](https://www.python.org/) 2 or 3 and [virtualenvwrapper](https://virtualenvwrapper.readthedocs.io/en/latest/) installed, just issue:
```
mkvirtualenv sparkmage
workon sparkmage
git clone [email protected]:policratus/sparkmage.git
cd sparkmage
pip install -r requirements/requirements.txt
```
## ⚙Usage
Sparmage needs [Hadoop](https://hadoop.apache.org/) (HDFS) (tested on 2.7) and [Spark](http://spark.apache.org/) (tested on 2.1) cluster as a distributed file system and processor.
### 🎯Acquiring images
All images are imported from [Google Images](https://images.google.com). To use a specific term and download images from this term:
```
sparkmage get [term] [directory]
```
For instance, if you wish to search for dogs, just issue `sparkmage get dogs /path/to/dogs/`
### 💽Storing images
All images are first stored on local file system and after this, it's uploaded to Hadoop HDFS. To copy images from a local directory to HDFS:
```
sparkmage put http://[host]:[port] [user] [local-dir] [hdfs-dir]
```
If you want to upload your just downloaded dog images, assuming that your HDFS endpoint is `master:50070`, user owner will be `hadoop`, and your target directory is `/images/dogs`, execute `sparkmage put http://master:50070 hadoop /path/to/dogs /images/dogs`.
### 📊Analyzing images
Now, comes the time to analyze all images and separate it in groups. Just execute:
```
sparkmage analyze hdfs://[host]:[port]/path/on/hdfs \
hdfs://[host]:[port]/cluster/output/dir \
[number_of_groups]
```
To analyze your just uploaded dog images and find five groups on it, execute `sparkmage analyze hdfs://master:50070/images/dogs hdfs://master:50070/clusters/dogs/clusters.out 5`.
### 👁Visualizing groups
So this is the final step: see your images and find what group it pertains. Do this:
```
sparkmage save http://[host]:[port] [user] [local-dir] http://[host]:[port]/cluster/output/dir
```
For instance, to cluster your dogs images: `sparkmage save http://master:50070 hadoop /path/to/dogs http://master:50070/clusters/dogs/clusters.out`.
The cluster that image pertains will be put inside the image itself, as a watermark.