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code.v1.dodo.cloud / pcloud / 8e060f8af01b3bcee957db66584eae6bcbb8483e
commit8e060f8af01b3bcee957db66584eae6bcbb8483e[log] [tgz]
authorgiolekva <giolekva@gmail.com>Mon May 04 16:52:34 2020 +0400
committergiolekva <giolekva@gmail.com>Mon May 04 16:52:34 2020 +0400
treebd52c5ed6a8fa7fcc5ccf0e48e333ba7e37de65f
parent437ef0722083b262e2f5524ea003b92c1babd9aa [diff]
event-processor: split go get from go build
1 file changed
tree: bd52c5ed6a8fa7fcc5ccf0e48e333ba7e37de65f
  1. apps/
  2. archive/
  3. controller/
  4. docs/
  5. events/
  6. scripts/
  7. .gitignore
  8. README.md
README.md

PCloud

PCloud is a set of distributed infrustructure tools meant for setting up a personal cloud on commodity hardware such as Raspberry Pi. Goal of the project is to provide:

  • Blob storage: distributed file storage with configurable replication for redundancy
  • Namespace service: built on top of Blob storage to expose it, at least in read only mode, as a mountable file system
  • Metadata service: storing Blob annotations such as objects and their locations detected in the pictures
  • Search infrastructure: to index Blob metadata and provide search API
  • App infrastructure: to easily set up and run third party applications such as custom in picture object detection models

To prove viability of the project first milestone will be to build fully functional image storage and indexing infrustructure. User experience setting it up will look something like:

  • Set up PCloud on 3 or more servers and pair mobile device with it
  • Configure IFTTT (if this then that) like worklfow to automatically:
    • Back up every newly taken picture on PCloud
    • Run face detection app on backed up pictures and store this information in Metadata service
    • Index face annotations and make them searchable

User must be able to configure all of these from previously paired mobile device.