new style model: new datasets

app.py

@@ -7,10 +7,11 @@ import numpy as np
 
 def is_cat(x): return x[0].isupper()
 
-learn = load_learner('styles20230416.pkl')
+learn = load_learner('export.pkl')
 
 #categories = ('cool-colors', 'earth-tones', 'jewel', 'neutral-colors', 'pastel', 'warm-colors')
-categories = ('classic', 'coastal', 'contamporary', 'industrial', 'midcentury', 'pacific-northwest', 'shabby chic')
+
+categories = ('classic', 'coastal', 'contemporary', 'industrial', 'midcentury', 'pacific-northwest', 'shabby chic')
 def classify_image(img):
     pred, idx, probs = learn.predict(img)
     return dict(zip(categories, map(float, probs)))

export.pkl

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:e975047632d3c69f2aedf9843d3298c9c2837be33b46044ada0d2296fd97cffa
-size 47286379
+oid sha256:cb6b11ad4d623a21260f936444ecf40302710bbd162839616a5de294ce6c0ea2
+size 48966187

styles20230416.pkl

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:b814950da10bf313d094fd746ad261eaeb2fba7c175295488b09391212ff26d9
-size 47503403