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name: "PVANET" | |
################################################################################ | |
## Input | |
################################################################################ | |
input: "data" | |
input_shape { | |
dim: 1 | |
dim: 3 |
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name: "PVANET finetune" | |
layer { | |
name: 'input-data' | |
type: 'Python' | |
top: 'data' | |
top: 'im_info' | |
top: 'gt_boxes' | |
python_param { | |
module: 'roi_data_layer.layer' | |
layer: 'RoIDataLayer' |
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name: "PVANet train" | |
layer { | |
name: 'input-data' | |
type: 'Python' | |
top: 'data' | |
top: 'im_info' | |
top: 'gt_boxes' | |
python_param { | |
module: 'roi_data_layer.layer' | |
layer: 'RoIDataLayer' |
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name: "PVANET test" | |
################################################################################ | |
## Input | |
################################################################################ | |
input: "data" | |
input_shape { | |
dim: 1 | |
dim: 3 |
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name: "VGG_ILSVRC_16_layers" | |
layer { | |
name: 'input-data' | |
type: 'Python' | |
top: 'data' | |
top: 'im_info' | |
top: 'gt_boxes' | |
python_param { | |
module: 'roi_data_layer.layer' | |
layer: 'RoIDataLayer' |
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name: "VGG_ILSVRC_16_layers" | |
layer { | |
name: 'input-data' | |
type: 'Python' | |
top: 'data' | |
top: 'im_info' | |
top: 'gt_boxes' | |
python_param { | |
module: 'roi_data_layer.layer' | |
layer: 'RoIDataLayer' |
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1. clone analytics-zoo project | |
```bash | |
git clone https://github.com/intel-analytics/analytics-zoo.git | |
``` | |
2. install image transformer library | |
``` | |
# mvn install image transformer lib | |
cd transform/vision | |
mvn clean install |
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from bigdl.util.common import * | |
init_engine() |
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import cv2 | |
folder = "images" | |
imageFiles = os.listdir(folder) | |
images = [] | |
for f in imageFiles: | |
image = cv2.imread(folder + '/' + f) | |
images.append(image) | |
img_rdd = sc.parallelize(images) |
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from bigdl.nn.layer import Model | |
# load model | |
model = Model.load("bigdl_mobilenet.model") | |
print 'load model done' |
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