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diff --git a/README.md b/README.md new file mode 100644 index 0000000..5fe2e5e --- /dev/null +++ b/README.md @@ -0,0 +1,99 @@ +Image Recognition Engine +======================== + +This is sample HTTP service for object detection using the +[YOLO](https://pjreddie.com/darknet/yolo/) model. +It comes with simple Web interface. + + +Requirements +============ + +IRE is written in Haskell with [GHC](http://www.haskell.org/ghc/). +All required Haskell libraries are listed in [ire.cabal](ire.cabal). +Use [cabal-install](http://www.haskell.org/haskellwiki/Cabal-Install) +to fetch and build all pre-requisites automatically. + +It also uses modified [Darknet library](https://github.com/ip1981/darknet), +which you have to build and install separately. + + +Installation +============ + + $ git clone https://github.com/ip1981/ire.git + $ cd ire + $ cabal install --ghc-options="-optl=-Wl,-rpath,$darknet/lib" --extra-include-dirs "$darknet/include" --extra-lib-dirs "$darknet/lib" + + +Usage +===== + +Type `ire --help` to see usage summary: + + Usage: + ire [options] + + Options: + -c, --config=FILE Configuration file [default: ire.yml] + + -r, --rootdir=DIR Web root directory with static files [default: <cabal datadir>] + -h, --help Show this message + + Note: + The default configuration file is loaded if found, + otherwise default built-in settings are used. + + + +Configuration +============= + +You have to provide network configuration file, weights file and class names. +See [example configuration file](./ire.example.yml) and Darknet source code. + + +Running +======= + +``` +$ ire +layer filters size input output + 0 conv 32 3 x 3 / 1 416 x 416 x 3 -> 416 x 416 x 32 + 1 max 2 x 2 / 2 416 x 416 x 32 -> 208 x 208 x 32 + 2 conv 64 3 x 3 / 1 208 x 208 x 32 -> 208 x 208 x 64 + 3 max 2 x 2 / 2 208 x 208 x 64 -> 104 x 104 x 64 + 4 conv 128 3 x 3 / 1 104 x 104 x 64 -> 104 x 104 x 128 + 5 conv 64 1 x 1 / 1 104 x 104 x 128 -> 104 x 104 x 64 + 6 conv 128 3 x 3 / 1 104 x 104 x 64 -> 104 x 104 x 128 + 7 max 2 x 2 / 2 104 x 104 x 128 -> 52 x 52 x 128 + 8 conv 256 3 x 3 / 1 52 x 52 x 128 -> 52 x 52 x 256 + 9 conv 128 1 x 1 / 1 52 x 52 x 256 -> 52 x 52 x 128 + 10 conv 256 3 x 3 / 1 52 x 52 x 128 -> 52 x 52 x 256 + 11 max 2 x 2 / 2 52 x 52 x 256 -> 26 x 26 x 256 + 12 conv 512 3 x 3 / 1 26 x 26 x 256 -> 26 x 26 x 512 + 13 conv 256 1 x 1 / 1 26 x 26 x 512 -> 26 x 26 x 256 + 14 conv 512 3 x 3 / 1 26 x 26 x 256 -> 26 x 26 x 512 + 15 conv 256 1 x 1 / 1 26 x 26 x 512 -> 26 x 26 x 256 + 16 conv 512 3 x 3 / 1 26 x 26 x 256 -> 26 x 26 x 512 + 17 max 2 x 2 / 2 26 x 26 x 512 -> 13 x 13 x 512 + 18 conv 1024 3 x 3 / 1 13 x 13 x 512 -> 13 x 13 x1024 + 19 conv 512 1 x 1 / 1 13 x 13 x1024 -> 13 x 13 x 512 + 20 conv 1024 3 x 3 / 1 13 x 13 x 512 -> 13 x 13 x1024 + 21 conv 512 1 x 1 / 1 13 x 13 x1024 -> 13 x 13 x 512 + 22 conv 1024 3 x 3 / 1 13 x 13 x 512 -> 13 x 13 x1024 + 23 conv 1024 3 x 3 / 1 13 x 13 x1024 -> 13 x 13 x1024 + 24 conv 1024 3 x 3 / 1 13 x 13 x1024 -> 13 x 13 x1024 + 25 route 16 + 26 reorg / 2 26 x 26 x 512 -> 13 x 13 x2048 + 27 route 26 24 + 28 conv 1024 3 x 3 / 1 13 x 13 x3072 -> 13 x 13 x1024 + 29 conv 425 1 x 1 / 1 13 x 13 x1024 -> 13 x 13 x 425 + 30 detection +Loading weights from yolo.weights...Done! +INFO: Listening on localhost:8080 +DEBUG: [Item {itemClass = 0, itemName = "person", itemConfidence = 0.8008945, itemBox = (0.3574012,0.42719698,0.6506731,0.24371791)},Item {itemClass = 16, itemName = "dog", itemConfidence = 0.6505284, itemBox = (0.6375929,0.5701367,0.21318695,0.15970974)}] +... +``` + + |