Merge pull request #482 from shelhamer/rcnn-detector-example

Make R-CNN the Caffe detection example

2 files changed, 234 insertions, 0 deletions

diff --git a/examples/imagenet/get_caffe_rcnn_imagenet_model.sh b/examples/imagenet/get_caffe_rcnn_imagenet_model.sh
new file mode 100755
index 00000000..7cd47fa3
--- /dev/null
+++ b/examples/imagenet/get_caffe_rcnn_imagenet_model.sh
@@ -0,0 +1,27 @@
+#!/usr/bin/env sh
+# This scripts downloads the Caffe R-CNN ImageNet
+# for ILSVRC13 detection.
+
+MODEL=caffe_rcnn_imagenet_model
+CHECKSUM=42c1556d2d47a9128c4a90e0a9c5341c
+
+if [ -f $MODEL ]; then
+  echo "Model already exists. Checking md5..."
+  os=`uname -s`
+  if [ "$os" = "Linux" ]; then
+    checksum=`md5sum $MODEL | awk '{ print $1 }'`
+  elif [ "$os" = "Darwin" ]; then
+    checksum=`cat $MODEL | md5`
+  fi
+  if [ "$checksum" = "$CHECKSUM" ]; then
+    echo "Model checksum is correct. No need to download."
+    exit 0
+  else
+    echo "Model checksum is incorrect. Need to download again."
+  fi
+fi
+
+echo "Downloading..."
+
+wget --no-check-certificate https://www.dropbox.com/s/0i3etlgmsmgf5ei/$MODEL
+echo "Done. Please run this command again to verify that checksum = $CHECKSUM."
diff --git a/examples/imagenet/rcnn_imagenet_deploy.prototxt b/examples/imagenet/rcnn_imagenet_deploy.prototxt
new file mode 100644
index 00000000..ef75a0a5
--- /dev/null
+++ b/examples/imagenet/rcnn_imagenet_deploy.prototxt
@@ -0,0 +1,207 @@
+name: "R-CNN-ilsvrc13"
+input: "data"
+input_dim: 10
+input_dim: 3
+input_dim: 227
+input_dim: 227
+layers {
+  name: "conv1"
+  type: CONVOLUTION
+  bottom: "data"
+  top: "conv1"
+  convolution_param {
+    num_output: 96
+    kernel_size: 11
+    stride: 4
+  }
+}
+layers {
+  name: "relu1"
+  type: RELU
+  bottom: "conv1"
+  top: "conv1"
+}
+layers {
+  name: "pool1"
+  type: POOLING
+  bottom: "conv1"
+  top: "pool1"
+  pooling_param {
+    pool: MAX
+    kernel_size: 3
+    stride: 2
+  }
+}
+layers {
+  name: "norm1"
+  type: LRN
+  bottom: "pool1"
+  top: "norm1"
+  lrn_param {
+    local_size: 5
+    alpha: 0.0001
+    beta: 0.75
+  }
+}
+layers {
+  name: "conv2"
+  type: CONVOLUTION
+  bottom: "norm1"
+  top: "conv2"
+  convolution_param {
+    num_output: 256
+    pad: 2
+    kernel_size: 5
+    group: 2
+  }
+}
+layers {
+  name: "relu2"
+  type: RELU
+  bottom: "conv2"
+  top: "conv2"
+}
+layers {
+  name: "pool2"
+  type: POOLING
+  bottom: "conv2"
+  top: "pool2"
+  pooling_param {
+    pool: MAX
+    kernel_size: 3
+    stride: 2
+  }
+}
+layers {
+  name: "norm2"
+  type: LRN
+  bottom: "pool2"
+  top: "norm2"
+  lrn_param {
+    local_size: 5
+    alpha: 0.0001
+    beta: 0.75
+  }
+}
+layers {
+  name: "conv3"
+  type: CONVOLUTION
+  bottom: "norm2"
+  top: "conv3"
+  convolution_param {
+    num_output: 384
+    pad: 1
+    kernel_size: 3
+  }
+}
+layers {
+  name: "relu3"
+  type: RELU
+  bottom: "conv3"
+  top: "conv3"
+}
+layers {
+  name: "conv4"
+  type: CONVOLUTION
+  bottom: "conv3"
+  top: "conv4"
+  convolution_param {
+    num_output: 384
+    pad: 1
+    kernel_size: 3
+    group: 2
+  }
+}
+layers {
+  name: "relu4"
+  type: RELU
+  bottom: "conv4"
+  top: "conv4"
+}
+layers {
+  name: "conv5"
+  type: CONVOLUTION
+  bottom: "conv4"
+  top: "conv5"
+  convolution_param {
+    num_output: 256
+    pad: 1
+    kernel_size: 3
+    group: 2
+  }
+}
+layers {
+  name: "relu5"
+  type: RELU
+  bottom: "conv5"
+  top: "conv5"
+}
+layers {
+  name: "pool5"
+  type: POOLING
+  bottom: "conv5"
+  top: "pool5"
+  pooling_param {
+    pool: MAX
+    kernel_size: 3
+    stride: 2
+  }
+}
+layers {
+  name: "fc6"
+  type: INNER_PRODUCT
+  bottom: "pool5"
+  top: "fc6"
+  inner_product_param {
+    num_output: 4096
+  }
+}
+layers {
+  name: "relu6"
+  type: RELU
+  bottom: "fc6"
+  top: "fc6"
+}
+layers {
+  name: "drop6"
+  type: DROPOUT
+  bottom: "fc6"
+  top: "fc6"
+  dropout_param {
+    dropout_ratio: 0.5
+  }
+}
+layers {
+  name: "fc7"
+  type: INNER_PRODUCT
+  bottom: "fc6"
+  top: "fc7"
+  inner_product_param {
+    num_output: 4096
+  }
+}
+layers {
+  name: "relu7"
+  type: RELU
+  bottom: "fc7"
+  top: "fc7"
+}
+layers {
+  name: "drop7"
+  type: DROPOUT
+  bottom: "fc7"
+  top: "fc7"
+  dropout_param {
+    dropout_ratio: 0.5
+  }
+}
+# R-CNN classification layer made from R-CNN ILSVRC13 SVMs.
+layers {
+  name: "fc-rcnn"
+  type: INNER_PRODUCT
+  bottom: "fc7"
+  top: "fc-rcnn"
+  inner_product_param {
+    num_output: 200
+  }
+}