feat: add utility file

README.md

@@ -9,6 +9,6 @@ app_file: app.py
 pinned: false
 license: apache-2.0
 short_description: Character captcha recognition using a CNN Transformer.
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+models:
+  - krishnatherokar/captcha-recognition
+---

utils.py

@@ -0,0 +1,38 @@
+import numpy as np
+import keras
+from keras.ops import ctc_decode
+
+HEIGHT = 50
+WIDTH = 200
+
+characters = "ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789"
+num_classes = len(characters)
+char_to_num = {char: i for i, char in enumerate(characters)}
+num_to_char = {i: char for i, char in enumerate(characters)}
+
+def process_images(img):
+    img = img.convert("L")
+    img = img.resize((WIDTH, HEIGHT))
+    img = np.array(img) / 255.0
+    return img
+
+base_model = keras.saving.load_model("hf://krishnatherokar/captcha-recognition")
+
+def predict_and_decode(img):
+    # preprocess
+    processed_image = process_images(img)
+    test_input = np.expand_dims([processed_image], axis=-1)
+
+    # predict
+    preds = base_model.predict(test_input)
+
+    input_len = np.ones(preds.shape[0]) * preds.shape[1]
+    decode = ctc_decode(
+        preds,
+        sequence_lengths=input_len,
+        strategy='greedy'
+    )[0][0]
+
+    for result in decode:
+        text = "".join([num_to_char[int(x)] for x in result if x >= 0 and x < num_classes])
+        return text