| import gradio as gr |
| import numpy as np |
| from keras.api.models import load_model |
| import string |
|
|
| class TextTypeLangModel: |
| def __init__(self, model_path, csv_path=None): |
| |
| self.model = load_model(model_path) |
| self.characters = string.ascii_letters + string.digits + " " + \ |
| "آبپچڈڑڤکگہہٹژزسٹطظعغفقکگلاںمںنۓہھوؤ" + \ |
| "ےیئؤٹپجچحخدڈذرزسشصضطظعغفقکلمنوٕں" + \ |
| "ۓۓہ۔،؛؟" |
|
|
| self.num_chars = len(self.characters) + 1 |
| self.char_to_index = {c: i+1 for i, c in enumerate(self.characters)} |
| self.index_to_char = {i+1: c for i, c in enumerate(self.characters)} |
|
|
| def encode_text(self, text, max_len=10): |
| text = text[:max_len].ljust(max_len) |
| return [self.char_to_index.get(c, 0) for c in text] |
|
|
| def preprocess_image(self, image): |
| |
| image = image.convert("RGB") |
| image = image.resize((128, 128)) |
| image = np.array(image) / 255.0 |
| return image |
|
|
| def predict(self, image): |
| image = self.preprocess_image(image) |
| image = np.expand_dims(image, axis=0) |
| pred_text, pred_type, pred_lang = self.model.predict(image) |
|
|
| |
| pred_text = ''.join(self.index_to_char.get(np.argmax(pred_text[0][i]), '') for i in range(10)) |
|
|
| return pred_text.strip(), np.argmax(pred_type), np.argmax(pred_lang) |
|
|
| def get_type_string(int_type): |
| type_switch = { |
| 0: "Medicine", |
| 1: "Dosage", |
| 2: "Diagnostic", |
| 3: "Symptoms", |
| 4: "Personal Info", |
| 5: "Numeric Data", |
| 6: "Text" |
| } |
| return type_switch.get(int_type, "Unknown") |
|
|
| def predict_text_type_lang(image): |
| model = TextTypeLangModel("./model/text_type_lang_model.h5") |
| predicted_text, predicted_type, predicted_language = model.predict(image) |
| predicted_type_str = get_type_string(predicted_type) |
| predicted_language_str = "English" if predicted_language == 0 else "Urdu" |
|
|
| return predicted_text, predicted_type_str, predicted_language_str |
|
|
| |
| iface = gr.Interface( |
| fn=predict_text_type_lang, |
| inputs=gr.Image(type="pil"), |
| outputs=["text", "text", "text"], |
| title="Text Type & Language Prediction", |
| description="Upload an image to predict the extracted text, type, and language.", |
| ) |
|
|
| iface.launch(debug=True) |
