sdf

Author: hereariim

blossom/api.py

@@ -35,7 +35,6 @@
 
 import numpy as np
 import imageio
-import matplotlib.pyplot as plt
 
 from itertools import chain
 from skimage.morphology import label
@@ -219,6 +218,12 @@ def get_train_args():
     }
     return arg_dict
 
+def warm():
+    try:
+        print("cc")
+    except Exception as e:
+        print(e)
+
 def train(**args):
     output={}
     output["hyperparameter"]=args
@@ -234,7 +239,7 @@ def train(**args):
 
     try:
         image_dir = tempfile.TemporaryDirectory()
-        # mount_nextcloud('rshare:/data/dataset_files', paths.get_splits_dir())
+        
         mount_nextcloud('rshare:/data/images', os.path.join(image_dir.name,'images'))
         print(">> RSHARE",os.listdir(os.path.join(image_dir.name,'images')))        
     except Exception as e:

blossom/config.py

@@ -29,48 +29,47 @@
 DATA_MASK = os.path.join(DATA_DIR,os.path.join('train','masks'))
 
 
-# Input parameters for predict() (deepaas>=1.0.0)
-class PredictArgsSchema(Schema):
-    class Meta:
-        unknown = INCLUDE  # support 'full_paths' parameter
+# # Input parameters for predict() (deepaas>=1.0.0)
+# class PredictArgsSchema(Schema):
+#     class Meta:
+#         unknown = INCLUDE  # support 'full_paths' parameter
 
-    # full list of fields: https://marshmallow.readthedocs.io/en/stable/api_reference.html
-    # to be able to upload a file for prediction
-    files = fields.Field(
-        required=False,
-        missing=None,
-        type="file",
-        data_key="data",
-        location="form",
-        description="Select a file for the prediction"
-    )
+#     # full list of fields: https://marshmallow.readthedocs.io/en/stable/api_reference.html
+#     # to be able to upload a file for prediction
+#     files = fields.Field(
+#         required=False,
+#         missing=None,
+#         type="file",
+#         data_key="data",
+#         location="form",
+#         description="Select a file for the prediction"
+#     )
 
-    # to be able to provide an URL for prediction
-    urls = fields.Url(
-        required=False,
-        missing=None,
-        description="Provide an URL of the data for the prediction"
-    )
+#     # to be able to provide an URL for prediction
+#     urls = fields.Url(
+#         required=False,
+#         missing=None,
+#         description="Provide an URL of the data for the prediction"
+#     )
 
-    # an input parameter for prediction
-    arg1 = fields.Integer(
-        required=False,
-        missing=1,
-        description="Input argument 1 for the prediction"
-    )
+#     # an input parameter for prediction
+#     arg1 = fields.Integer(
+#         required=False,
+#         missing=1,
+#         description="Input argument 1 for the prediction"
+#     )
 
-# Input parameters for train() (deepaas>=1.0.0)
-class TrainArgsSchema(Schema):
-    class Meta:
-        unknown = INCLUDE  # support 'full_paths' parameter
+# # Input parameters for train() (deepaas>=1.0.0)
+# class TrainArgsSchema(Schema):
+#     class Meta:
+#         unknown = INCLUDE  # support 'full_paths' parameter
 
-    # available fields are e.g. fields.Integer(), fields.Str(), fields.Boolean()
-    # full list of fields: https://marshmallow.readthedocs.io/en/stable/api_reference.html
-    arg1 = fields.Integer(
-        required=False,
-        missing=1,
-        description="Input argument 1 for training"
-    )
-
-#additional
+#     # available fields are e.g. fields.Integer(), fields.Str(), fields.Boolean()
+#     # full list of fields: https://marshmallow.readthedocs.io/en/stable/api_reference.html
+#     arg1 = fields.Integer(
+#         required=False,
+#         missing=1,
+#         description="Input argument 1 for training"
+#     )
 
+# #additional

blossom/path.py

@@ -19,6 +19,6 @@ def get_data_dir():
 def get_logs_dir():
     return os.path.join(get_models_dir(),"logs")
 
-print(os.path.abspath(os.path.join(homedir, base_dir)))
-print(os.path.join(get_base_dir(),os.path.join('blossom','models')))
-print(os.path.join(get_base_dir(),os.path.join('blossom','dataset')))
+print(">",os.path.abspath(os.path.join(homedir, base_dir)))
+print(">",os.path.join(get_base_dir(),os.path.join('blossom','models')))
+print(">",os.path.join(get_base_dir(),os.path.join('blossom','dataset')))

requirements.txt

@@ -16,9 +16,12 @@ numpy
 tensorflow
 focal_loss
 scikit-image
-scikit-learn
+sklearn
 h5py
 imshowpair
 gdown
 tqdm
-pydrive
+pydrive
+SciPy
+joblib
+threadpoolctl

setup.cfg

@@ -23,7 +23,6 @@ packages =
     blossom
 
 [entry_points]
-
 deepaas.v2.model = 
     blossom = blossom.api