paths ...

.gitattributes

@@ -6,5 +6,5 @@
 *.css filter=lfs diff=lfs merge=lfs -text
 *.pt filter=lfs diff=lfs merge=lfs -text
 *.sh filter=lfs diff=lfs merge=lfs -text
-/SOURCE/yolo_files/utils/google_app_engine/Dockerfile filter=lfs diff=lfs merge=lfs -text
+/utils/google_app_engine/Dockerfile filter=lfs diff=lfs merge=lfs -text
 *.pth filter=lfs diff=lfs merge=lfs -text

pages/3_Signify.py

@@ -10,7 +10,7 @@ import torchvision.transforms as transforms
 from PIL import Image
 from signify.siamese import SiameseNetwork
 
-#from SOURCE.yolo_files import detect
+#from import detect
 
 MEDIA_ROOT = 'results/media/signatures/'
 SIGNATURE_ROOT = 'results/media/UserSignaturesSquare/'

signify/gan/data/__init__.py

@@ -24,7 +24,7 @@ def find_dataset_using_name(dataset_name):
     be instantiated. It has to be a subclass of BaseDataset,
     and it is case-insensitive.
     """
-    dataset_filename = "SOURCE.gan_files.data." + dataset_name + "_dataset"
+    dataset_filename = "data." + dataset_name + "_dataset"
     datasetlib = importlib.import_module(dataset_filename)
 
     dataset = None

signify/gan/data/aligned_dataset.py

@@ -1,7 +1,13 @@
+import sys
+
+sys.path.append("signify/gan")
+
 import os
-from SOURCE.gan_files.data.base_dataset import BaseDataset, get_params, get_transform
-from SOURCE.gan_files.data.image_folder import make_dataset
+
 from PIL import Image
+from data.base_dataset import (BaseDataset, get_params,
+                                                get_transform)
+from data.image_folder import make_dataset
 
 
 class AlignedDataset(BaseDataset):

signify/gan/data/colorization_dataset.py

@@ -1,10 +1,15 @@
+import sys
+
+sys.path.append("signify/gan")
+
 import os
-from SOURCE.gan_files.data.base_dataset import BaseDataset, get_transform
-from SOURCE.gan_files.data.image_folder import make_dataset
-from skimage import color  # require skimage
-from PIL import Image
+
 import numpy as np
 import torchvision.transforms as transforms
+from PIL import Image
+from skimage import color  # require skimage
+from data.base_dataset import BaseDataset, get_transform
+from data.image_folder import make_dataset
 
 
 class ColorizationDataset(BaseDataset):

signify/gan/data/single_dataset.py

@@ -1,6 +1,10 @@
-from SOURCE.gan_files.data.base_dataset import BaseDataset, get_transform
-from SOURCE.gan_files.data.image_folder import make_dataset
+import sys
+
+sys.path.append("signify/gan")
+
 from PIL import Image
+from data.base_dataset import BaseDataset, get_transform
+from data.image_folder import make_dataset
 
 
 class SingleDataset(BaseDataset):

signify/gan/data/template_dataset.py

@@ -11,7 +11,12 @@ You need to implement the following functions:
     -- <__getitem__>: Return a data point and its metadata information.
     -- <__len__>: Return the number of images.
 """
-from SOURCE.gan_files.data.base_dataset import BaseDataset, get_transform
+import sys
+
+sys.path.append("signify/gan")
+
+from data.base_dataset import BaseDataset, get_transform
+
 # from data.image_folder import make_dataset
 # from PIL import Image
 

signify/gan/data/unaligned_dataset.py

@@ -1,9 +1,14 @@
+import sys
+
+sys.path.append("signify/gan")
+
 import os
-from SOURCE.gan_files.data.base_dataset import BaseDataset, get_transform
-from SOURCE.gan_files.data.image_folder import make_dataset
-from PIL import Image
 import random
 
+from PIL import Image
+from data.base_dataset import BaseDataset, get_transform
+from data.image_folder import make_dataset
+
 
 class UnalignedDataset(BaseDataset):
     """

signify/gan/models/__init__.py

@@ -30,7 +30,7 @@ def find_model_using_name(model_name):
     be instantiated. It has to be a subclass of BaseModel,
     and it is case-insensitive.
     """
-    model_filename = "SOURCE.gan_files.models." + model_name + "_model"
+    model_filename = "models." + model_name + "_model"
     modellib = importlib.import_module(model_filename)
     model = None
     target_model_name = model_name.replace('_', '') + 'model'

signify/gan/models/base_model.py

@@ -1,8 +1,13 @@
+import sys
+
+sys.path.append("signify/gan")
+
 import os
-import torch
-from collections import OrderedDict
 from abc import ABC, abstractmethod
-from SOURCE.gan_files.models import networks
+from collections import OrderedDict
+
+import torch
+from models import networks
 
 
 class BaseModel(ABC):

signify/gan/models/colorization_model.py

@@ -1,7 +1,11 @@
+import sys
+
+sys.path.append("signify/gan")
+
 import numpy as np
 import torch
 from skimage import color  # used for lab2rgb
-from SOURCE.gan_files.models.pix2pix_model import Pix2PixModel
+from models.pix2pix_model import Pix2PixModel
 
 
 class ColorizationModel(Pix2PixModel):

signify/gan/models/cycle_gan_model.py

@@ -1,8 +1,13 @@
-import torch
+import sys
+
+sys.path.append("signify/gan")
+
 import itertools
+
+import torch
+from models import networks
+from models.base_model import BaseModel
 from util.image_pool import ImagePool
-from SOURCE.gan_files.models.base_model import BaseModel
-from SOURCE.gan_files.models import networks
 
 
 class CycleGANModel(BaseModel):

signify/gan/models/pix2pix_model.py

@@ -1,6 +1,10 @@
+import sys
+
+sys.path.append("signify/gan")
+
 import torch
-from SOURCE.gan_files.models.base_model import BaseModel
-from SOURCE.gan_files.models import networks
+from models import networks
+from models.base_model import BaseModel
 
 
 class Pix2PixModel(BaseModel):

signify/gan/models/template_model.py

@@ -15,9 +15,13 @@ You need to implement the following functions:
     <forward>: Run forward pass. This will be called by both <optimize_parameters> and <test>.
     <optimize_parameters>: Update network weights; it will be called in every training iteration.
 """
+import sys
+
+sys.path.append("signify/gan")
+
 import torch
-from SOURCE.gan_files.models.base_model import BaseModel
-from SOURCE.gan_files.models import networks
+from models import networks
+from models.base_model import BaseModel
 
 
 class TemplateModel(BaseModel):

signify/gan/models/test_model.py

@@ -1,5 +1,9 @@
-from SOURCE.gan_files.models.base_model import BaseModel
-from SOURCE.gan_files.models import networks
+import sys
+
+sys.path.append("signify/gan")
+
+from models import networks
+from models.base_model import BaseModel
 
 
 class TestModel(BaseModel):

signify/gan/options/base_options.py

@@ -1,9 +1,14 @@
+import sys
+
+sys.path.append("signify/gan")
+
 import argparse
 import os
-from SOURCE.gan_files.util import util
+
+import data as data
+import models as models
 import torch
-import SOURCE.gan_files.models as models
-import SOURCE.gan_files.data as data
+from util import util
 
 
 class BaseOptions():
@@ -24,7 +29,7 @@ class BaseOptions():
         # parser.add_argument('--dataroot', required=True, help='path to images (should have subfolders trainA, trainB, valA, valB, etc)')
         parser.add_argument('--name', type=str, default='gan_signdata_kaggle', help='name of the experiment. It decides where to store samples and models')
         parser.add_argument('--gpu_ids', type=str, default='0', help='gpu ids: e.g. 0  0,1,2, 0,2. use -1 for CPU') 
-        parser.add_argument('--checkpoints_dir', type=str, default='SOURCE/gan_files/checkpoints/', help='models are saved here')
+        parser.add_argument('--checkpoints_dir', type=str, default='checkpoints/', help='models are saved here')
         # model parameters
         parser.add_argument('--model', type=str, default='test', help='chooses which model to use. [cycle_gan | pix2pix | test | colorization]')
         parser.add_argument('--input_nc', type=int, default=3, help='# of input image channels: 3 for RGB and 1 for grayscale')

signify/gan/options/test_options.py

@@ -1,5 +1,10 @@
 # from .base_options import BaseOptions
-from SOURCE.gan_files.options.base_options import BaseOptions
+import sys
+
+sys.path.append("signify/gan")
+
+from options.base_options import BaseOptions
+
 
 class TestOptions(BaseOptions):
     """This class includes test options.

signify/gan/options/train_options.py

@@ -1,4 +1,8 @@
-from SOURCE.gan_files.options.base_options import BaseOptions
+import sys
+
+sys.path.append("signify/gan")
+
+from options.base_options import BaseOptions
 
 
 class TrainOptions(BaseOptions):

signify/gan/util/visualizer.py

@@ -1,11 +1,15 @@
-import numpy as np
-import os
 import sys
+
+sys.path.append("signify/gan")
+
 import ntpath
+import os
+import sys
 import time
-from SOURCE.gan_files.util import util, html
-from subprocess import Popen, PIPE
+from subprocess import PIPE, Popen
 
+import numpy as np
+from util import html, util
 
 if sys.version_info[0] == 2:
     VisdomExceptionBase = Exception

signify/yolo/detect.py

@@ -1,5 +1,4 @@
 import sys
-
 sys.path.append("signify/yolo")
 
 
@@ -24,7 +23,7 @@ from utils.torch_utils import load_classifier, select_device, time_synchronized
 
 def detect(image_path):
     opt = {
-    'weights': 'SOURCE/yolo_files/best.pt',
+    'weights': 'best.pt',
     'source': image_path,
     'img_size': 640,
     'conf_thres': 0.25,

signify/yolo/models/common.py

@@ -12,10 +12,10 @@ import torch.nn as nn
 from PIL import Image
 from torch.cuda import amp
 
-from SOURCE.yolo_files.utils.datasets import letterbox
-from SOURCE.yolo_files.utils.general import non_max_suppression, make_divisible, scale_coords, increment_path, xyxy2xywh, save_one_box
-from SOURCE.yolo_files.utils.plots import colors, plot_one_box
-from SOURCE.yolo_files.utils.torch_utils import time_synchronized
+from utils.datasets import letterbox
+from utils.general import non_max_suppression, make_divisible, scale_coords, increment_path, xyxy2xywh, save_one_box
+from utils.plots import colors, plot_one_box
+from utils.torch_utils import time_synchronized
 
 
 def autopad(k, p=None):  # kernel, padding

signify/yolo/models/experimental.py

@@ -1,11 +1,12 @@
 # YOLOv5 experimental modules
+import sys
+sys.path.append("signify/yolo")
 
 import numpy as np
 import torch
 import torch.nn as nn
-
-from SOURCE.yolo_files.models.common import Conv, DWConv
-from SOURCE.yolo_files.utils.google_utils import attempt_download
+from models.common import Conv, DWConv
+from utils.google_utils import attempt_download
 
 
 class CrossConv(nn.Module):
@@ -111,7 +112,7 @@ class Ensemble(nn.ModuleList):
 
 
 def attempt_load(weights, map_location=None, inplace=True):
-    from SOURCE.yolo_files.models.yolo import Detect, Model
+    from models.yolo import Detect, Model
 
     # Loads an ensemble of models weights=[a,b,c] or a single model weights=[a] or weights=a
     model = Ensemble()

signify/yolo/models/export.py

@@ -3,6 +3,9 @@
 Usage:
     $ export PYTHONPATH="$PWD" && python models/export.py --weights yolov5s.pt --img 640 --batch 1
 """
+import sys
+
+sys.path.append("signify/yolo")
 
 import argparse
 import sys
@@ -11,16 +14,17 @@ from pathlib import Path
 
 sys.path.append(Path(__file__).parent.parent.absolute().__str__())  # to run '$ python *.py' files in subdirectories
 
+import models
 import torch
 import torch.nn as nn
+from models.experimental import attempt_load
+from utils.activations import Hardswish, SiLU
+from utils.general import (check_img_size,
+                                             check_requirements, colorstr,
+                                             file_size, set_logging)
+from utils.torch_utils import select_device
 from torch.utils.mobile_optimizer import optimize_for_mobile
 
-import SOURCE.yolo_files.models
-from SOURCE.yolo_files.models.experimental import attempt_load
-from SOURCE.yolo_files.utils.activations import Hardswish, SiLU
-from SOURCE.yolo_files.utils.general import colorstr, check_img_size, check_requirements, file_size, set_logging
-from SOURCE.yolo_files.utils.torch_utils import select_device
-
 if __name__ == '__main__':
     parser = argparse.ArgumentParser()
     parser.add_argument('--weights', type=str, default='./yolov5s.pt', help='weights path')

signify/yolo/models/yolo.py

@@ -9,11 +9,14 @@ from pathlib import Path
 sys.path.append(Path(__file__).parent.parent.absolute().__str__())  # to run '$ python *.py' files in subdirectories
 logger = logging.getLogger(__name__)
 
-from SOURCE.yolo_files.models.common import *
-from SOURCE.yolo_files.models.experimental import *
-from SOURCE.yolo_files.utils.autoanchor import check_anchor_order
-from SOURCE.yolo_files.utils.general import make_divisible, check_file, set_logging
-from SOURCE.yolo_files.utils.torch_utils import time_synchronized, fuse_conv_and_bn, model_info, scale_img, initialize_weights, \
+import sys
+sys.path.append("signify/yolo")
+
+from models.common import *
+from models.experimental import *
+from utils.autoanchor import check_anchor_order
+from utils.general import make_divisible, check_file, set_logging
+from utils.torch_utils import time_synchronized, fuse_conv_and_bn, model_info, scale_img, initialize_weights, \
     select_device, copy_attr
 
 try:

signify/yolo/utils/autoanchor.py

@@ -5,7 +5,7 @@ import torch
 import yaml
 from tqdm import tqdm
 
-from SOURCE.yolo_files.utils.general import colorstr
+from utils.general import colorstr
 
 
 def check_anchor_order(m):

signify/yolo/utils/general.py

@@ -20,9 +20,9 @@ import torch
 import torchvision
 import yaml
 
-from SOURCE.yolo_files.utils.google_utils import gsutil_getsize
-from SOURCE.yolo_files.utils.metrics import fitness
-from SOURCE.yolo_files.utils.torch_utils import init_torch_seeds
+from utils.google_utils import gsutil_getsize
+from utils.metrics import fitness
+from utils.torch_utils import init_torch_seeds
 
 # Settings
 torch.set_printoptions(linewidth=320, precision=5, profile='long')

signify/yolo/utils/loss.py

@@ -3,8 +3,8 @@
 import torch
 import torch.nn as nn
 
-from SOURCE.yolo_files.utils.general import bbox_iou
-from SOURCE.yolo_files.utils.torch_utils import is_parallel
+from utils.general import bbox_iou
+from utils.torch_utils import is_parallel
 
 
 def smooth_BCE(eps=0.1):  # https://github.com/ultralytics/yolov3/issues/238#issuecomment-598028441

signify/yolo/utils/plots.py

@@ -17,8 +17,8 @@ import torch
 import yaml
 from PIL import Image, ImageDraw, ImageFont
 
-from SOURCE.yolo_files.utils.general import xywh2xyxy, xyxy2xywh
-from SOURCE.yolo_files.utils.metrics import fitness
+from utils.general import xywh2xyxy, xyxy2xywh
+from utils.metrics import fitness
 
 # Settings
 matplotlib.rc('font', **{'size': 11})