ui

app.py

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+import gradio as gr
+from transformers import pipeline
+import os
+import deepl
+import openai
+from PIL import Image
+import requests
+from io import BytesIO
+
+TARGET_LANG = "EN-GB"
+
+deepl_key = os.environ.get('DEEPL')
+openai.api_key = os.environ.get('OPENAI')
+
+whisper = pipeline(model="openai/whisper-small")  # change to "your-username/the-name-you-picked"
+translator = deepl.Translator(deepl_key)
+
+
+def transcribe(audio):
+    text_sv = whisper(audio)["text"]
+    print(f"Audio transcribed: {text_sv}")
+    text_en = translator.translate_text(text_sv, target_lang=TARGET_LANG).text
+    print(f"Text translated: {text_en}")
+    res = openai.Image.create(
+        prompt=text_en,
+        n=1,
+        size="512x512"
+    )
+    img_url = res['data'][0]['url']
+    print(f"Image generated: {img_url}")
+    response = requests.get(img_url)
+    img = Image.open(BytesIO(response.content))
+
+    return text_sv, text_en, img
+
+
+iface = gr.Interface(
+    fn=transcribe,
+    inputs=gr.Audio(source="microphone", type="filepath"),
+    outputs=[gr.Textbox(label="Transcribed text"),
+             gr.Textbox(label="English translation"),
+             gr.Image(type="pil", label="Output image")],
+    title="Swedish speech to image",
+    description="You may have heard of text to image, or speach to text, but have you heard of speech to image? Now you have!",
+)
+
+iface.launch()

requirements.txt

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+hopsworks
+joblib
+scikit-learn