Fix some flake8 errors in cleanup and nsfw_detect

Just some minor code cleanup

cleanup.py

@@ -18,7 +18,10 @@
     and limitations under the License.
 """
 
-import os, sys, time, datetime
+import os
+import sys
+import time
+import datetime
 from fhost import app
 
 os.chdir(os.path.dirname(sys.argv[0]))
@@ -33,7 +36,7 @@ maxd = 365
 for f in files:
     stat = os.stat(f)
     systime = time.time()
-    age = datetime.timedelta(seconds = systime - stat.st_mtime).days
+    age = datetime.timedelta(seconds=(systime - stat.st_mtime)).days
 
     maxage = mind + (-maxd + mind) * (stat.st_size / maxs - 1) ** 3
 

nsfw_detect.py

@@ -24,21 +24,30 @@ import sys
 from io import BytesIO
 from subprocess import run, PIPE, DEVNULL
 
-os.environ["GLOG_minloglevel"] = "2" # seriously :|
 import caffe
 
+os.environ["GLOG_minloglevel"] = "2"  # seriously :|
+
+
 class NSFWDetector:
     def __init__(self):
 
         npath = os.path.join(os.path.dirname(__file__), "nsfw_model")
-        self.nsfw_net = caffe.Net(os.path.join(npath, "deploy.prototxt"),
+        self.nsfw_net = caffe.Net(
-                                  os.path.join(npath, "resnet_50_1by2_nsfw.caffemodel"),
+            os.path.join(npath, "deploy.prototxt"),
-                                  caffe.TEST)
+            os.path.join(npath, "resnet_50_1by2_nsfw.caffemodel"),
-        self.caffe_transformer = caffe.io.Transformer({'data': self.nsfw_net.blobs['data'].data.shape})
+            caffe.TEST)
-        self.caffe_transformer.set_transpose('data', (2, 0, 1))  # move image channels to outermost
+        self.caffe_transformer = caffe.io.Transformer({
-        self.caffe_transformer.set_mean('data', np.array([104, 117, 123]))  # subtract the dataset-mean value in each channel
+            'data': self.nsfw_net.blobs['data'].data.shape
-        self.caffe_transformer.set_raw_scale('data', 255)  # rescale from [0, 1] to [0, 255]
+        })
-        self.caffe_transformer.set_channel_swap('data', (2, 1, 0))  # swap channels from RGB to BGR
+        # move image channels to outermost
+        self.caffe_transformer.set_transpose('data', (2, 0, 1))
+        # subtract the dataset-mean value in each channel
+        self.caffe_transformer.set_mean('data', np.array([104, 117, 123]))
+        # rescale from [0, 1] to [0, 255]
+        self.caffe_transformer.set_raw_scale('data', 255)
+        # swap channels from RGB to BGR
+        self.caffe_transformer.set_channel_swap('data', (2, 1, 0))
 
     def _compute(self, img):
         image = caffe.io.load_image(BytesIO(img))
@@ -54,8 +63,8 @@ class NSFWDetector:
 
         input_name = self.nsfw_net.inputs[0]
         output_layers = ["prob"]
-        all_outputs = self.nsfw_net.forward_all(blobs=output_layers,
+        all_outputs = self.nsfw_net.forward_all(
-                    **{input_name: transformed_image})
+            blobs=output_layers, **{input_name: transformed_image})
 
         outputs = all_outputs[output_layers[0]][0].astype(float)
 
@@ -63,7 +72,10 @@ class NSFWDetector:
 
     def detect(self, fpath):
         try:
-            ff = run(["ffmpegthumbnailer", "-m", "-o-", "-s256", "-t50%", "-a", "-cpng", "-i", fpath], stdout=PIPE, stderr=DEVNULL, check=True)
+            ff = run([
+                "ffmpegthumbnailer", "-m", "-o-", "-s256", "-t50%", "-a",
+                "-cpng", "-i", fpath
+            ], stdout=PIPE, stderr=DEVNULL, check=True)
             image_data = ff.stdout
         except:
             return -1.0
@@ -72,6 +84,7 @@ class NSFWDetector:
 
         return scores[1]
 
+
 if __name__ == "__main__":
     n = NSFWDetector()