Update app.py

app.py

@@ -20,18 +20,16 @@ prediction_model = keras.models.Model(
 with open("vocab.txt", "r") as f:
     vocab = f.read().splitlines()
 
-# Mapping integers back to original characters
 num_to_char = layers.StringLookup(
     vocabulary=vocab, mask_token=None, invert=True
 )
 
 def decode_batch_predictions(pred):
     input_len = np.ones(pred.shape[0]) * pred.shape[1]
-    # Use greedy search. For complex tasks, you can use beam search
     results = keras.backend.ctc_decode(pred, input_length=input_len, greedy=True)[0][0][
         :, :max_length
     ]
-    # Iterate over the results and get back the text
+    
     output_text = []
     for res in results:
         res = tf.strings.reduce_join(num_to_char(res)).numpy().decode("utf-8")
@@ -39,16 +37,10 @@ def decode_batch_predictions(pred):
     return output_text
 
 def classify_image(img_path):
-    # 1. Read image
     img = tf.io.read_file(img_path)
-    # 2. Decode and convert to grayscale
     img = tf.io.decode_png(img, channels=1)
-    # 3. Convert to float32 in [0, 1] range
     img = tf.image.convert_image_dtype(img, tf.float32)
-    # 4. Resize to the desired size
     img = tf.image.resize(img, [img_height, img_width])
-    # 5. Transpose the image because we want the time
-    # dimension to correspond to the width of the image.
     img = tf.transpose(img, perm=[1, 0, 2])
     img = tf.expand_dims(img, axis=0)
     preds = prediction_model.predict(img)
@@ -59,9 +51,9 @@ image = gr.inputs.Image(type='filepath')
 text = gr.outputs.Textbox()
 
 iface = gr.Interface(classify_image,image,text,
-  title="OCR for CAPTCHA",
-	description = "Keras Implementation of OCR model for reading captcha 🤖🦹🏻",
-        article = "Author: <a href=\"https://huggingface.co/anuragshas\">Anurag Singh</a>. Based on the keras example from <a href=\"https://keras.io/examples/vision/captcha_ocr/\">A_K_Nain</a>",
+  title="un-captcha",
+	description = "Recognizes captcha text (pictures)|Распознает текст капчи (картинки)",
+        article = "Сюды: https://huggingface.co/DarkyMan/",
         examples = ["dd764.png","3p4nn.png"]
 )