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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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