diff options
Diffstat (limited to 'Codes')
| -rw-r--r-- | Codes/evaluate.py | 15 | ||||
| -rw-r--r-- | Codes/inference-test.py | 21 | ||||
| -rw-r--r-- | Codes/test.sh | 12 | ||||
| -rw-r--r-- | Codes/train.sh | 6 | ||||
| -rw-r--r-- | Codes/training_hyper_params/hyper_params.ini | 46 | ||||
| -rw-r--r-- | Codes/utils.py | 2 |
6 files changed, 92 insertions, 10 deletions
diff --git a/Codes/evaluate.py b/Codes/evaluate.py index cd0fcef..4909e50 100644 --- a/Codes/evaluate.py +++ b/Codes/evaluate.py @@ -114,8 +114,10 @@ class GroundTruthLoader(object): gt = self.__load_shanghaitech_gt() elif dataset == GroundTruthLoader.TOY_DATA: gt = self.__load_toydata_gt() + #else: + # gt = self.__load_ucsd_avenue_subway_gt(dataset) else: - gt = self.__load_ucsd_avenue_subway_gt(dataset) + gt = self.__load_no_anomaly_gt(dataset) return gt def __load_ucsd_avenue_subway_gt(self, dataset): @@ -200,6 +202,15 @@ class GroundTruthLoader(object): return gt @staticmethod + def __load_no_anomaly_gt(): + gt = [] + for i in xrange(27): + length = 64 + video_gt = np.zeros((length,), dtype=np.uint8) + gt.append(video_gt) + return gt + + @staticmethod def get_pixel_masks_file_list(dataset): # pixel mask folder pixel_mask_folder = os.path.join(DATA_DIR, dataset, 'pixel_masks') @@ -573,4 +584,4 @@ if __name__ == '__main__': if eval_type == 'test_func': test_func() else: - evaluate(eval_type, file_path)
\ No newline at end of file + evaluate(eval_type, file_path) diff --git a/Codes/inference-test.py b/Codes/inference-test.py index b16a56c..83a4fd4 100644 --- a/Codes/inference-test.py +++ b/Codes/inference-test.py @@ -10,6 +10,7 @@ from utils import DataLoader, load, save, psnr_error from constant import const import evaluate +from PIL import Image slim = tf.contrib.slim @@ -66,6 +67,7 @@ with tf.Session(config=config) as sess: load(loader, sess, ckpt) output_records = [] + outputs = [] videos_info = data_loader.videos num_videos = len(videos_info.keys()) total = 0 @@ -78,15 +80,19 @@ with tf.Session(config=config) as sess: for i in range(num_his, length): video_clip = data_loader.get_video_clips(video_name, i - num_his, i + 1) - output, psnr = sess.run([test_outputs, test_psnr_error] + output, psnr = sess.run([test_outputs, test_psnr_error], feed_dict={test_video_clips_tensor: video_clip[np.newaxis, ...]}) - outputs[i] = output + outputs.append(output) - tf.image.encode_png( - output, - compression=-1, - name=None - ) + #tf.image.encode_png( + # output, + # compression=-1, + # name=None + #) + ohhh = (output[0,...] + 1.0) * 127.5 + print(ohhh.shape, np.amin(ohhh), np.amax(ohhh)) + out = Image.fromarray(ohhh, 'RGB') + out.save(os.path.join(os.getcwd(), '{}_{:05d}.png'.format(video_name, i))) print('video = {} / {}, i = {} / {}, psnr = {:.6f}'.format( video_name, num_videos, i, length, psnr)) @@ -108,6 +114,7 @@ with tf.Session(config=config) as sess: # print(results) + print(os.path.isdir(snapshot_dir)) if os.path.isdir(snapshot_dir): def check_ckpt_valid(ckpt_name): is_valid = False diff --git a/Codes/test.sh b/Codes/test.sh new file mode 100644 index 0000000..a683a5a --- /dev/null +++ b/Codes/test.sh @@ -0,0 +1,12 @@ +#python inference-test.py --dataset kaulsdorf_gray \ +# --train_folder /home/lens/Desktop/thumbs/kaulsdorf_gray/Train/ \ +# --test_folder /home/lens/Desktop/thumbs/kaulsdorf_gray/Test/ \ +# --snapshot_dir ./checkpoints/kaulsdorf_gray_l_2_alpha_1_lp_1.0_adv_0.05_gdl_1.0_flow_0.01/model.ckpt-140000 \ +# --gpu 0 + +python inference-test.py --dataset kaulsdorf_single \ + --train_folder /home/lens/code/Adversarial_Video_Generation/Data/kaulsdorf_single/Train/ \ + --test_folder /home/lens/code/Adversarial_Video_Generation/Data/kaulsdorf_single/Test/ \ + --snapshot_dir ./checkpoints/kaulsdorf_single_l_2_alpha_1_lp_0.001_adv_0.05_gdl_1.0_flow_2.0/model.ckpt-19000 \ + --gpu 0 + diff --git a/Codes/train.sh b/Codes/train.sh new file mode 100644 index 0000000..3145aa9 --- /dev/null +++ b/Codes/train.sh @@ -0,0 +1,6 @@ +python train.py --dataset kaulsdorf_gray \ + --train_folder /home/lens/Desktop/thumbs/kaulsdorf_gray/Train/ \ + --test_folder /home/lens/Desktop/thumbs/kaulsdorf_gray/Test/ \ + --gpu 0 \ + --iters 500000 + diff --git a/Codes/training_hyper_params/hyper_params.ini b/Codes/training_hyper_params/hyper_params.ini index f7868f1..963902c 100644 --- a/Codes/training_hyper_params/hyper_params.ini +++ b/Codes/training_hyper_params/hyper_params.ini @@ -41,6 +41,52 @@ LRATE_D = [0.00001, 0.000001] LRATE_D_BOUNDARIES = [40000] +[kaulsdorf_gray] +# for lp loss. e.g, 1 or 2 for l1 and l2 loss, respectively) +L_NUM = 2 +# the power to which each gradient term is raised in GDL loss +ALPHA_NUM = 1 +# the percentage of the adversarial loss to use in the combined loss +LAM_ADV = 0.05 +# the percentage of the lp loss to use in the combined loss +LAM_LP = 1 +# the percentage of the GDL loss to use in the combined loss +LAM_GDL = 1 +# the percentage of the different frame loss, LAM_FLOW = 2 is also ok, but LAM_FLOW = 0.01 is slightly better. +LAM_FLOW = 0.01 + +# For gray scale video, such as Ped2 and Ped1, learning rate of G and D star from 1e-4 and 1e-5, respectively. +LRATE_G = [0.0001, 0.00001] +LRATE_G_BOUNDARIES = [40000] + +LRATE_D = [0.00001, 0.000001] +LRATE_D_BOUNDARIES = [40000] + + +[kaulsdorf_single] +# for lp loss. e.g, 1 or 2 for l1 and l2 loss, respectively) +L_NUM = 2 +# the power to which each gradient term is raised in GDL loss +ALPHA_NUM = 1 +# the percentage of the adversarial loss to use in the combined loss +LAM_ADV = 0.05 +# the percentage of the lp loss to use in the combined loss, +# we found in smaller lp is slightly better in avenue, but not too much difference +# LAM_LP = 1 is 84.9, LAM_LP = 0.001 may arrive to 85.1 +LAM_LP = 0.001 +# the percentage of the GDL loss to use in the combined loss +LAM_GDL = 1 +# the percentage of the different frame loss +LAM_FLOW = 2 + +# For rgb color scale video, such as Ped2 and Ped1, learning rate of G and D star from 2e-4 and 2e-5, respectively. +LRATE_G = [0.0002, 0.00002] +LRATE_G_BOUNDARIES = [100000] + +LRATE_D = [0.00002, 0.000002] +LRATE_D_BOUNDARIES = [100000] + + [avenue] # for lp loss. e.g, 1 or 2 for l1 and l2 loss, respectively) L_NUM = 2 diff --git a/Codes/utils.py b/Codes/utils.py index 8466d08..7f54fe7 100644 --- a/Codes/utils.py +++ b/Codes/utils.py @@ -76,7 +76,7 @@ class DataLoader(object): video_name = video.split('/')[-1] self.videos[video_name] = {} self.videos[video_name]['path'] = video - self.videos[video_name]['frame'] = glob.glob(os.path.join(video, '*.jpg')) + self.videos[video_name]['frame'] = glob.glob(os.path.join(video, '*.png')) self.videos[video_name]['frame'].sort() self.videos[video_name]['length'] = len(self.videos[video_name]['frame']) |