Update app.py

app.py

@@ -1,154 +1,95 @@
 import gradio as gr
 import numpy as np
-import random
-
-# import spaces #[uncomment to use ZeroGPU]
-from diffusers import DiffusionPipeline
-import torch
-
-device = "cuda" if torch.cuda.is_available() else "cpu"
-model_repo_id = "stabilityai/sdxl-turbo"  # Replace to the model you would like to use
-
-if torch.cuda.is_available():
-    torch_dtype = torch.float16
-else:
-    torch_dtype = torch.float32
-
-pipe = DiffusionPipeline.from_pretrained(model_repo_id, torch_dtype=torch_dtype)
-pipe = pipe.to(device)
-
-MAX_SEED = np.iinfo(np.int32).max
-MAX_IMAGE_SIZE = 1024
-
-
-# @spaces.GPU #[uncomment to use ZeroGPU]
-def infer(
-    prompt,
-    negative_prompt,
-    seed,
-    randomize_seed,
-    width,
-    height,
-    guidance_scale,
-    num_inference_steps,
-    progress=gr.Progress(track_tqdm=True),
-):
-    if randomize_seed:
-        seed = random.randint(0, MAX_SEED)
-
-    generator = torch.Generator().manual_seed(seed)
-
-    image = pipe(
-        prompt=prompt,
-        negative_prompt=negative_prompt,
-        guidance_scale=guidance_scale,
-        num_inference_steps=num_inference_steps,
-        width=width,
-        height=height,
-        generator=generator,
-    ).images[0]
-
-    return image, seed
-
-
-examples = [
-    "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k",
-    "An astronaut riding a green horse",
-    "A delicious ceviche cheesecake slice",
-]
-
-css = """
-#col-container {
-    margin: 0 auto;
-    max-width: 640px;
+import sounddevice as sd
+import scipy.io.wavfile as wavfile
+
+# Morse code dictionary
+MORSE_CODE_DICT = {
+    'A': '.-', 'B': '-...', 'C': '-.-.', 'D': '-..', 'E': '.', 'F': '..-.', 'G': '--.', 'H': '....',
+    'I': '..', 'J': '.---', 'K': '-.-', 'L': '.-..', 'M': '--', 'N': '-.', 'O': '---', 'P': '.--.',
+    'Q': '--.-', 'R': '.-.', 'S': '...', 'T': '-', 'U': '..-', 'V': '...-', 'W': '.--', 'X': '-..-',
+    'Y': '-.--', 'Z': '--..', '0': '-----', '1': '.----', '2': '..---', '3': '...--', '4': '....-',
+    '5': '.....', '6': '-....', '7': '--...', '8': '---..', '9': '----.', ' ': ' '
 }
-"""
-
-with gr.Blocks(css=css) as demo:
-    with gr.Column(elem_id="col-container"):
-        gr.Markdown(" # Text-to-Image Gradio Template")
-
-        with gr.Row():
-            prompt = gr.Text(
-                label="Prompt",
-                show_label=False,
-                max_lines=1,
-                placeholder="Enter your prompt",
-                container=False,
-            )
-
-            run_button = gr.Button("Run", scale=0, variant="primary")
-
-        result = gr.Image(label="Result", show_label=False)
-
-        with gr.Accordion("Advanced Settings", open=False):
-            negative_prompt = gr.Text(
-                label="Negative prompt",
-                max_lines=1,
-                placeholder="Enter a negative prompt",
-                visible=False,
-            )
-
-            seed = gr.Slider(
-                label="Seed",
-                minimum=0,
-                maximum=MAX_SEED,
-                step=1,
-                value=0,
-            )
-
-            randomize_seed = gr.Checkbox(label="Randomize seed", value=True)
-
-            with gr.Row():
-                width = gr.Slider(
-                    label="Width",
-                    minimum=256,
-                    maximum=MAX_IMAGE_SIZE,
-                    step=32,
-                    value=1024,  # Replace with defaults that work for your model
-                )
-
-                height = gr.Slider(
-                    label="Height",
-                    minimum=256,
-                    maximum=MAX_IMAGE_SIZE,
-                    step=32,
-                    value=1024,  # Replace with defaults that work for your model
-                )
-
-            with gr.Row():
-                guidance_scale = gr.Slider(
-                    label="Guidance scale",
-                    minimum=0.0,
-                    maximum=10.0,
-                    step=0.1,
-                    value=0.0,  # Replace with defaults that work for your model
-                )
-
-                num_inference_steps = gr.Slider(
-                    label="Number of inference steps",
-                    minimum=1,
-                    maximum=50,
-                    step=1,
-                    value=2,  # Replace with defaults that work for your model
-                )
 
-        gr.Examples(examples=examples, inputs=[prompt])
-    gr.on(
-        triggers=[run_button.click, prompt.submit],
-        fn=infer,
-        inputs=[
-            prompt,
-            negative_prompt,
-            seed,
-            randomize_seed,
-            width,
-            height,
-            guidance_scale,
-            num_inference_steps,
-        ],
-        outputs=[result, seed],
+def text_to_morse(text):
+    """Convert text to Morse code."""
+    text = text.upper()
+    morse = []
+    for char in text:
+        if char in MORSE_CODE_DICT:
+            morse.append(MORSE_CODE_DICT[char])
+        else:
+            morse.append('?')
+    return ' '.join(morse)
+
+def generate_morse_audio(morse_text, frequency=800, wpm=20, sample_rate=44100):
+    """Generate audio for Morse code."""
+    # Timing calculations based on WPM (words per minute)
+    dit_duration = 1.2 / wpm  # Duration of a dit in seconds
+    dah_duration = 3 * dit_duration  # Duration of a dah
+    space_duration = dit_duration  # Space between symbols
+    word_space_duration = 7 * dit_duration  # Space between words
+
+    # Generate audio samples
+    t = np.linspace(0, 1, int(sample_rate * 1), endpoint=False)
+    tone = np.sin(2 * np.pi * frequency * t)
+
+    audio = []
+    for symbol in morse_text:
+        if symbol == '.':
+            # Dit: short beep
+            audio.extend(tone[:int(sample_rate * dit_duration)])
+        elif symbol == '-':
+            # Dah: long beep
+            audio.extend(tone[:int(sample_rate * dah_duration)])
+        elif symbol == ' ':
+            # Space between words
+            audio.extend(np.zeros(int(sample_rate * word_space_duration)))
+        # Space between symbols
+        if symbol != ' ':
+            audio.extend(np.zeros(int(sample_rate * space_duration)))
+
+    audio = np.array(audio)
+    # Normalize audio to prevent clipping
+    audio = audio / np.max(np.abs(audio)) * 0.8
+    # Save to WAV file
+    output_file = "morse_audio.wav"
+    wavfile.write(output_file, sample_rate, audio.astype(np.float32))
+    return output_file
+
+def convert_to_morse_and_audio(input_text, frequency, wpm):
+    """Convert text to Morse code and generate audio."""
+    if not input_text:
+        return "Please enter some text.", None
+    
+    # Convert text to Morse code
+    morse_text = text_to_morse(input_text)
+    # Generate audio
+    audio_file = generate_morse_audio(morse_text, frequency, wpm)
+    return morse_text, audio_file
+
+# Gradio Blocks UI
+with gr.Blocks(title="Text to Morse Code Audio Converter") as demo:
+    gr.Markdown("# Text to Morse Code Audio Converter")
+    gr.Markdown("Enter text to convert it to Morse code and generate an audio file.")
+    
+    with gr.Row():
+        with gr.Column():
+            text_input = gr.Textbox(label="Input Text", placeholder="Enter text (e.g., SOS)")
+            frequency = gr.Slider(400, 1200, value=800, step=10, label="Audio Frequency (Hz)")
+            wpm = gr.Slider(5, 40, value=20, step=1, label="Speed (Words Per Minute)")
+            convert_button = gr.Button("Convert")
+        
+        with gr.Column():
+            morse_output = gr.Textbox(label="Morse Code", interactive=False)
+            audio_output = gr.Audio(label="Morse Code Audio", interactive=False)
+    
+    convert_button.click(
+        fn=convert_to_morse_and_audio,
+        inputs=[text_input, frequency, wpm],
+        outputs=[morse_output, audio_output]
     )
 
 if __name__ == "__main__":
-    demo.launch()
+    demo.launch()