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CaitinZhao / cvpr2019_Pyramid-Feature-Attention-Network-for-Saliency-detection

code and model of Pyramid Feature Selective Network for Saliency detection
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Could you provide your trained model ? #4

Open happycoding1996 opened 5 years ago

happycoding1996 commented 5 years ago

Dear author,

Thanks for your great work !

Could you provide the trained VGG16 model that I want to directly test on my personal data ?

Thank you !

zwm19950414 commented 5 years ago

python train.py Using TensorFlow backend. train_file model/vgg16_no_top.h5 model_weights train_pair.txt 0 input_1 1 block1_conv1 2 block1_conv2 3 block1_pool 4 dropout_1 5 block2_conv1 6 block2_conv2 7 block2_pool 8 dropout_2 9 block3_conv1 10 block3_conv2 11 block3_conv3 12 block3_pool 13 dropout_3 14 block4_conv1 15 block4_conv2 16 block4_conv3 17 block4_pool 18 dropout_4 19 block5_conv1 20 block5_conv2 21 block5_conv3 22 dropout_5 23 C4_cfe_cfe0 24 C4_cfe_cfe1_dilation 25 C4_cfe_cfe2_dilation 26 C4_cfe_cfe3_dilation 27 C5_cfe_cfe0 28 C5_cfe_cfe1_dilation 29 C5_cfe_cfe2_dilation 30 C5_cfe_cfe3_dilation 31 C3_cfe_cfe0 32 C3_cfe_cfe1_dilation 33 C3_cfe_cfe2_dilation 34 C3_cfe_cfe3_dilation 35 C4_cfeconcatcfe 36 C5_cfeconcatcfe 37 C3_cfeconcatcfe 38 C4_cfe_BN 39 C5_cfe_BN 40 C3_cfe_BN 41 C4_cfe_relu 42 C5_cfe_relu 43 C3_cfe_relu 44 C4_cfe_up2 45 C5_cfe_up4 46 C345_aspp_concat 47 C345_ChannelWiseAttention_withcpfe_GlobalAveragePooling2D 48 dense_1 49 dense_2 50 C345_ChannelWiseAttention_withcpfe_reshape 51 C345_ChannelWiseAttention_withcpfe_repeat 52 C345_ChannelWiseAttention_withcpfe_multiply 53 C345_conv 54 C345_BN 55 C345_relu 56 C345_up4 57 spatial_attention_1_conv1 58 spatial_attention_2_conv1 59 attention1_1_BN 60 attention2_1_BN 61 C2_conv 62 attention1_1_relu 63 attention2_1_relu 64 C1_conv 65 C2_BN_BN 66 spatial_attention_1_conv2 67 spatial_attention_2_conv2 68 C1_BN_BN 69 C2_BN_relu 70 attention1_2_BN 71 attention2_2_BN 72 C1_BN_relu 73 C2_up2 74 attention1_2_relu 75 attention2_2_relu 76 C12_concat 77 spatial_attention_add 78 C12_conv 79 activation_1 80 C12_BN 81 repeat_1 82 C12_relu 83 C12_atten_mutiply 84 fuse_concat 85 sa Traceback (most recent call last): File "train.py", line 72, in model.load_weights(model_name,by_name=True) File "/home/lthpc/anaconda3/envs/py27/lib/python2.7/site-packages/keras/engine/topology.py", line 2566, in load_weights f = h5py.File(filepath, mode='r') File "/home/lthpc/anaconda3/envs/py27/lib/python2.7/site-packages/h5py/_hl/files.py", line 271, in init fid = make_fid(name, mode, userblock_size, fapl, swmr=swmr) File "/home/lthpc/anaconda3/envs/py27/lib/python2.7/site-packages/h5py/_hl/files.py", line 101, in make_fid fid = h5f.open(name, flags, fapl=fapl) File "h5py/_objects.pyx", line 54, in h5py._objects.with_phil.wrapper (/home/ilan/minonda/conda-bld/h5py_1490028130695/work/h5py/_objects.c:2846) File "h5py/_objects.pyx", line 55, in h5py._objects.with_phil.wrapper (/home/ilan/minonda/conda-bld/h5py_1490028130695/work/h5py/_objects.c:2804) File "h5py/h5f.pyx", line 78, in h5py.h5f.open (/home/ilan/minonda/conda-bld/h5py_1490028130695/work/h5py/h5f.c:2123) IOError: Unable to open file (File signature not found) What did you do about it？

guotengda111 commented 5 years ago

I

Dear author,

Thanks for your great work !

Could you provide the trained VGG16 model that I want to directly test on my personal data ?

Thank you !

Can you get the trained model ? I also want to directly test with the auther's model, if you have got it ,please share it to me. Thank you a lot!

zwm19950414 commented 5 years ago

Hello, can you read this code in data. py into the picture path in train - pair. txt? The code is as follows： def getTrainGenerator(file_path, target_size, batch_size, israndom=False): f = open(file_path, 'r') trainlist = f.readlines() f.close() while True: random.shuffle(trainlist) batch_x = [] batch_y = [] for name in trainlist: p = name.strip('\r\n').split(' ') img_path = p[0] mask_path = p[1] x = cv2.imread(img_path) y = cv2.imread(mask_path)

I directly gave a picture of the path, but ran for more than a day without output, how do you run? for name in trainlist:

p = name.strip('\r\n').split(' ')

        #img_path = p[0]
        img_path=‘/home/lthpc/cvpr/DUTS1/ILSVRC2012_test_00000003.jpg’
        #mask_path = p[1]
        mask_path =‘/home/lthpc/cvpr/DUTS2/ILSVRC2012_test_00000003.png’

------------------ 原始邮件 ------------------ 发件人: "guotengda111"notifications@github.com; 发送时间: 2019年6月2日(星期天) 上午10:33 收件人: "CaitinZhao/cvpr2019_Pyramid-Feature-Attention-Network-for-Saliency-detection"cvpr2019_Pyramid-Feature-Attention-Network-for-Saliency-detection@noreply.github.com; 抄送: "1789068711"1789068711@qq.com;"Comment"comment@noreply.github.com; 主题: Re:[CaitinZhao/cvpr2019_Pyramid-Feature-Attention-Network-for-Saliency-detection]Could you provide your trained model ? (#4)

I

Dear author,

Thanks for your great work !

Could you provide the trained VGG16 model that I want to directly test on my personal data ?

Thank you !

Can you get the trained mopdel ? I also want to directly test with the auther's model, if you have got it ,please share it to me. Thank you a lot!

— You are receiving this because you commented. Reply to this email directly, view it on GitHub, or mute the thread.

sairajk commented 5 years ago

Hi @happycoding1996 @guotengda111 and @zwm19950414 ,

You can check my PyTorch implementation of this paper here.