Python cvpr_12net示例

示例#1

文件： train_det.py 项目： ByungKeon-Ko/mlstudy_week7

print "Train DET net start, net : ", net_name
print "MODE_CONT : ", MODE_CONT
print "Learing Rate : ", LearningRate
print "nBatch : ", nBatch
# ############################################################################# #
# ---------------------- NETWORK MODEL ---------------------------------------- #
# ############################################################################# #
BM = batch_manager.BatchManager()
BM.init(net_name)

sess = tf.Session( config=tf.ConfigProto(gpu_options=gpu_options ) )
sess = tf.InteractiveSession()

if net_name == '12net' :
	N12 = cvpr_network.cvpr_12net()
	N12.input_config_noscale()
	N12.infer()
	N12.objective()
	N12.train(LearningRate, threshold)
	network_list = [N12]

elif net_name == '24net' :
	N12 = cvpr_network.cvpr_12net()
	N12.input_config_div2()
	N12.infer()
	N24 = cvpr_network.cvpr_24net()
	N24.input_config_noscale()
	N24.infer()
	N24.objective()
	N24.train(LearningRate, threshold)

示例#2

文件： eval_ccd.py 项目： ByungKeon-Ko/mlstudy_week7

threshold1 = 0.80
threshold2 = 0.90
threshold3 = 0.95
BigKernelSize = 100
MinFace = 48

gpu_options = tf.GPUOptions(per_process_gpu_memory_fraction=0.1 )

# ----------------------------------------- 

# ------ Network ------------------------
sess = tf.Session( config=tf.ConfigProto(gpu_options=gpu_options ) )
sess = tf.InteractiveSession()

N12 = cvpr_network.cvpr_12net()
N12.infer_scan(BigKernelSize)

N12_infer = cvpr_network.cvpr_12net()
N12_infer.infer()

N24 = cvpr_network.cvpr_24net()
# N24.infer_scan(BigKernelSize)
N24.infer()

N48 = cvpr_network.cvpr_48net()
# N48.infer_scan(BigKernelSize)
N48.infer()

# ------ Scanning ------------------------
saver1 = tf.train.Saver( { 'net48_w_conv1':N48.W_conv1, 'net48_b_conv1':N48.b_conv1, 'net48_w_conv2':N48.W_conv2, 'net48_b_conv2':N48.b_conv2, 'net48_w_fc1':N48.W_fc1, 'net48_b_fc1':N48.b_fc1, 'net48_w_fc2':N48.W_fc2, 'net48_b_fc2': N48.b_fc2 } )

示例#3

文件： PrepareNS_aflw.py 项目： honghuCode/mlstudy_week7

			if net_name == '24net' :
				path = "%s/NS_aflw24/ns-%d.jpg" %(base_path, cnt_ns+cnt_save)
			elif net_name == '48net' :
				path = "%s/NS_aflw48_1/ns-%d.jpg" %(base_path, cnt_ns+cnt_save)
			org_img = org_img.convert('RGB')
			image_search.save_patch(org_img, final_list[i], path, net_name)
			cnt_save = cnt_save + 1

	return cnt_save

# -----------------------------------------

sess = tf.Session( config=tf.ConfigProto(gpu_options=gpu_options ) )
sess = tf.InteractiveSession()

N12 = cvpr_network.cvpr_12net()
N12.input_config_noscale()
N12.infer()

CAL12 = cvpr_network.cvpr_calib_12net()
CAL12.input_config_noscale()
CAL12.infer()

saver1 = tf.train.Saver( { 'net12_w_conv1':N12.W_conv1, 'net12_b_conv1':N12.b_conv1, 'net12_w_fc1':N12.W_fc1, 'net12_b_fc1':N12.b_fc1, 'net12_w_fc2':N12.W_fc2, 'net12_b_fc2': N12.b_fc2 } )
saver1.restore(sess, ckpt_file1)
saver2 = tf.train.Saver( { 'cal12_w_conv1':CAL12.W_conv1, 'cal12_b_conv1':CAL12.b_conv1, 'cal12_w_fc1':CAL12.W_fc1, 'cal12_b_fc1':CAL12.b_fc1, 'cal12_w_fc2':CAL12.W_fc2, 'cal12_b_fc2': CAL12.b_fc2 } )
saver2.restore(sess, ckpt_file2)

if (net_name == '48net') :
	N24 = cvpr_network.cvpr_24net()
	N24.input_config_noscale()

示例#4

文件： eval_ccd.py 项目： honghuCode/mlstudy_week7

threshold1 = 0.80
threshold2 = 0.90
threshold3 = 0.95
BigKernelSize = 100
MinFace = 48

gpu_options = tf.GPUOptions(per_process_gpu_memory_fraction=0.1)

# -----------------------------------------

# ------ Network ------------------------
sess = tf.Session(config=tf.ConfigProto(gpu_options=gpu_options))
sess = tf.InteractiveSession()

N12 = cvpr_network.cvpr_12net()
N12.infer_scan(BigKernelSize)

N12_infer = cvpr_network.cvpr_12net()
N12_infer.infer()

N24 = cvpr_network.cvpr_24net()
# N24.infer_scan(BigKernelSize)
N24.infer()

N48 = cvpr_network.cvpr_48net()
# N48.infer_scan(BigKernelSize)
N48.infer()

# ------ Scanning ------------------------
saver1 = tf.train.Saver({