Single Shot MultiBox Detector implemented with TensorFlow
python3.6.1
- numpy
- skimage
- TensorFlow
- matplotlib
- OpenCV
- Import required modules
import tensorflow as tf
import numpy as np
from util.util import *
from model.SSD300 import *
- Load test-image
img = load_image('./test.jpg')
img = img.reshape((300, 300, 3))
- Start Session
with tf.Session() as sess:
ssd = SSD300(sess)
sess.run(tf.global_variables_initializer())
for ep in range(EPOCH):
...
- Training or Evaluating you must just call ssd.eval() !
...
_, _, batch_loc, batch_conf, batch_loss = ssd.eval(minibatch, actual_data, is_training=True)
...
you have to extract data-set from zip files. decompress all zip files in datasets/ and move to voc2007/ dir.
$ ls voc2007/ | wc -l # => 4954
$ ./setup.sh
$ python train.py
I'm checking and testing SSD model, so this model may not be complete.
If I have overlooked something, please tell me.