Added input mosaicing

app.py

@@ -5,8 +5,23 @@ import skimage
 learn = load_learner('panda-model-1')
 
 labels = learn.dls.vocab
+
+def get_crops(img):
+    tile_size = 250
+    img = np.array(img)
+    crop = np.array(img.shape) // tile_size * tile_size; crop
+    imgc = img[:crop[0],:crop[1]]
+    imgc = imgc.reshape(imgc.shape[0] // tile_size, tile_size, imgc.shape[1] // tile_size, tile_size, 3)
+    xs, ys = (imgc.mean(axis=1).mean(axis=2).mean(axis=-1) < 252).nonzero()
+    if len(xs) == 0:
+        xs, ys = (imgc.mean(axis=1).mean(axis=2).mean(axis=-1)).nonzero()
+#     if len(xs) < 2: print("no data in image:", x)
+    pidxs = random.choices(list(range(len(xs))), k=36)
+    return PILImage.create(imgc[xs[pidxs],:,ys[pidxs],:].reshape(6,6,tile_size,tile_size,3).transpose(0,2,1,3,4).reshape(6*tile_size,6*tile_size,3))
+#     return imgc.mean(axis=1).mean(axis=2).mean(axis=-1)
+
 def predict(img):
-    img = PILImage.create(img)
+    img = get_crops(PILImage.create(img))
     pred,pred_idx,probs = learn.predict(img)
     return {labels[i]: float(probs[i]) for i in range(len(labels))}