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| import gradio as gr | |
| from PIL import Image | |
| import os | |
| import random | |
| from transformers import pipeline | |
| from difflib import SequenceMatcher | |
| all_images = os.listdir("assets") | |
| current_image = None | |
| pipe = pipeline(model="DurreSudoku/whisper-small-sv") # change to "your-username/the-name-you-picked" | |
| def test_func(): | |
| random_int = random.randint(1, 100) | |
| string = "Test successful" + str(random_int) | |
| return string | |
| def empty_string(): | |
| return "" | |
| def open_image(): | |
| # Open a random image | |
| global all_images | |
| global current_image | |
| if len(all_images) == 0: | |
| all_images = os.listdir("assets") | |
| img_name = random.choice(all_images) | |
| all_images.remove(img_name) | |
| current_image = img_name | |
| img = Image.open(os.path.join(r"assets", img_name)) | |
| # print(img.filename) | |
| return img | |
| def transcribe(audio): | |
| # Transcribe the audio and split the string into a list of words | |
| try: | |
| transcribed_audio = pipe(audio)["text"] | |
| except: | |
| return "Encountered an error. Are you sure that you recorded audio before submitting?" | |
| transcribed_audio = transcribed_audio.replace(",", "") | |
| transcribed_audio = transcribed_audio.replace(".", "") | |
| transcribed_audio = transcribed_audio.replace("!", "") | |
| transcribed_audio = transcribed_audio.replace("?", "") | |
| transcribed_audio = transcribed_audio.lower() | |
| text_list = transcribed_audio.split(" ") | |
| correct_answer = current_image.split(".png")[0] | |
| # Check for a perfect match. | |
| if correct_answer in text_list: | |
| return f"Correct! The answer is {correct_answer}." | |
| # Check for partial match, in case the model mistakes a letter or two. | |
| for text in text_list: | |
| match_ratio = SequenceMatcher(None, text, correct_answer).ratio() | |
| if match_ratio >= 0.8: | |
| return f"The answer is {correct_answer}. I heard {text}." | |
| # If no match is found. | |
| return f"The correct answer is {correct_answer}. I heard {transcribed_audio}." | |
| with gr.Blocks(title="Interactive Language Learning") as demo: | |
| with gr.Row(): | |
| gr.Markdown( | |
| """ | |
| # Interactive Language Learning Prototype | |
| Hello! | |
| This is a prototype app that is meant to help you learn some basic Swedish words. Observe the image, | |
| record a one word answer and press the "Submit Answer" button! For a new image, press the "New Image" button. | |
| """) | |
| with gr.Row(): | |
| with gr.Column(): | |
| audio = gr.Audio(sources="microphone", type="filepath", label="Record your answer here") | |
| with gr.Column(): | |
| image = gr.Image(value=open_image(),type="pil", interactive=False) | |
| with gr.Row(): | |
| answer_box = gr.Text(label="Answer appears here", interactive=False) | |
| with gr.Row(): | |
| with gr.Column(): | |
| process_input = gr.Button("Submit Answer") | |
| process_input.click(fn=transcribe, inputs=audio, outputs=answer_box) | |
| # process_input.click(fn=test_func, inputs=None, outputs=answer_box) | |
| with gr.Column(): | |
| refresh = gr.Button("New Image") | |
| refresh.click(fn=open_image, inputs=None, outputs=image) | |
| refresh.click(fn=empty_string, inputs=None, outputs=answer_box) | |
| demo.launch(debug=True) |