ck196

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'

ck196

name: "toyota_SSD_500x500_train"
layer {
  name: "data"
  type: "AnnotatedData"
  top: "data"
  top: "label"
  include {
    phase: TRAIN
  }
  transform_param {

ck196

from __future__ import division, print_function, absolute_import
import pickle
import numpy as np 
from PIL import Image

import tflearn
from tflearn.layers.core import input_data, dropout, fully_connected
from tflearn.layers.conv import conv_2d, max_pool_2d
from tflearn.layers.normalization import local_response_normalization
from tflearn.layers.estimator import regression

ck196

name: "ResNet_VOC0712_SSD_300x300_train"
layer {
  name: "data"
  type: "AnnotatedData"
  top: "data"
  top: "label"
  include {
    phase: TRAIN
  }
  transform_param {

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import numpy as np
import matplotlib.pyplot as plt
#%matplotlib inline

import skimage
import skimage.io as skio

import os
from os import path

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name: "ResNet_VOC0712_SSD_500x500_train"
layer {
  name: "data"
  type: "AnnotatedData"
  top: "data"
  top: "label"
  include {
    phase: TRAIN
  }
  transform_param {

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from __future__ import division
import os
import math
import numpy as np
import json
from os import listdir
from os.path import isfile, join
#from nms.gpu_nms import gpu_nms
#import gpu_nms
import sys

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#!/bin/bash

set -x
set -e

LOG="testing_log.txt"
exec &> >(tee -a "$LOG")
echo Logging output to "$LOG"

rm -rf data/VOCdevkit2007/annotations_cache/annots.pkl

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Yêu cầu

• Ubuntu >= 14.04, GPU( >= 2GB), CUDA 7.5+, cuDnn 4.0.7+
• Install docker, docker-nvidia

Cài đặt

docker pull ck196/py-faster-rcnn

Download pre-trained model. https://drive.google.com/open?id=0B4MXf_cfl_weOEMyTHVSRWF6M0U

ck196

import numpy as np

# Make sure that caffe is on the python path:
# export PYTHONPATH=${CAFFE_ROOT}/python
import caffe
import cv2
 
class AgenDetector:

    gen_net = None