1 files changed, 5 insertions, 7 deletions

diff --git a/modules/textual_inversion/autocrop.py b/modules/textual_inversion/autocrop.py
index 68e1103c..7770d22f 100644
--- a/modules/textual_inversion/autocrop.py
+++ b/modules/textual_inversion/autocrop.py
@@ -1,10 +1,8 @@
 import cv2

 import requests

 import os

-from collections import defaultdict

-from math import log, sqrt

 import numpy as np

-from PIL import Image, ImageDraw

+from PIL import ImageDraw

 

 GREEN = "#0F0"

 BLUE = "#00F"

@@ -111,7 +109,7 @@ def focal_point(im, settings):
       if corner_centroid is not None:

         color = BLUE

         box = corner_centroid.bounding(max_size * corner_centroid.weight)

-        d.text((box[0], box[1]-15), "Edge: %.02f" % corner_centroid.weight, fill=color)

+        d.text((box[0], box[1]-15), f"Edge: {corner_centroid.weight:.02f}", fill=color)

         d.ellipse(box, outline=color)

         if len(corner_points) > 1:

           for f in corner_points:

@@ -119,7 +117,7 @@ def focal_point(im, settings):
       if entropy_centroid is not None:

         color = "#ff0"

         box = entropy_centroid.bounding(max_size * entropy_centroid.weight)

-        d.text((box[0], box[1]-15), "Entropy: %.02f" % entropy_centroid.weight, fill=color)

+        d.text((box[0], box[1]-15), f"Entropy: {entropy_centroid.weight:.02f}", fill=color)

         d.ellipse(box, outline=color)

         if len(entropy_points) > 1:

           for f in entropy_points:

@@ -127,7 +125,7 @@ def focal_point(im, settings):
       if face_centroid is not None:

         color = RED

         box = face_centroid.bounding(max_size * face_centroid.weight)

-        d.text((box[0], box[1]-15), "Face: %.02f" % face_centroid.weight, fill=color)

+        d.text((box[0], box[1]-15), f"Face: {face_centroid.weight:.02f}", fill=color)

         d.ellipse(box, outline=color)

         if len(face_points) > 1:

           for f in face_points:

@@ -185,7 +183,7 @@ def image_face_points(im, settings):
         try:

           faces = classifier.detectMultiScale(gray, scaleFactor=1.1,

             minNeighbors=7, minSize=(minsize, minsize), flags=cv2.CASCADE_SCALE_IMAGE)

-        except:

+        except Exception:

           continue

 

         if len(faces) > 0: