Duplicate from qiny17/ArtIstic-GENREator

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README.md

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+---
+title: ArtIstic GENREator
+emoji: 📈
+colorFrom: indigo
+colorTo: green
+sdk: gradio
+sdk_version: 3.12.0
+app_file: app.py
+pinned: false
+license: mit
+duplicated_from: qiny17/ArtIstic-GENREator
+---
+
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

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+import torch
+import gradio as gr
+from transformers import pipeline, T5ForConditionalGeneration, T5Tokenizer
+from diffusers import StableDiffusionPipeline, EulerDiscreteScheduler
+
+# generate lyrics
+lyrics_generator = pipeline("text-generation", "ECE1786-AG/lyrics-generator")
+
+# summarize lyrics
+model = T5ForConditionalGeneration.from_pretrained("Michau/t5-base-en-generate-headline")
+tokenizer = T5Tokenizer.from_pretrained("Michau/t5-base-en-generate-headline")
+
+# generate single cover
+scheduler = EulerDiscreteScheduler.from_pretrained("stabilityai/stable-diffusion-2", subfolder="scheduler")
+pipe = StableDiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-2", scheduler=scheduler, revision="fp16", torch_dtype=torch.float16)
+device = "cuda" if torch.cuda.is_available() else "cpu"
+pipe = pipe.to(device)
+
+def generate_lyrics(genre, prompt):
+  complete_prompt = "<BOS> <{0}>\n{1}".format(genre, prompt)
+  lyrics = lyrics_generator(complete_prompt, max_length=1024)
+  lyrics = lyrics[0]['generated_text']
+  lyrics = lyrics.split('\n', 1)[1] # remove first line from the generated lyrics
+  
+  return lyrics
+
+def summarize_lyrics(lyrics):
+  text =  "headline: " + lyrics
+  encoding = tokenizer.encode_plus(text, return_tensors = "pt")
+  input_ids = encoding["input_ids"]
+  attention_masks = encoding["attention_mask"]
+  beam_outputs = model.generate(
+      input_ids = input_ids,
+      attention_mask = attention_masks,
+      max_length = 100,
+      num_beams = 5,
+      early_stopping = True,
+  )
+  result = tokenizer.decode(beam_outputs[0])
+  result = result.replace('<pad>', '')
+  result = result.replace('</s>', '')
+
+  return result
+
+def generate_cover(prompt, style, effect):
+  prompt = summarize_lyrics(prompt) # call function summarize_lyrics to summarize lyrics
+  prompt = prompt + ", " + effect + ", album cover, artistic, " + style
+  print(prompt)
+  image = pipe(prompt).images[0]
+  return image
+
+demo = gr.Blocks()
+with demo:
+    gr.HTML(
+        """
+            <div style="text-align: center; max-width: 700px; margin: 0 auto;">
+              <div style="display: inline-flex; align-items: center; gap: 0.8rem; font-size: 1.75rem;">
+                <h1 style="font-weight: 900; margin-bottom: 7px;">ArtIstic GENREator</h1>
+              </div>
+              <p style="margin-bottom: 10px; font-size: 94%">Generate Inspirational Lyrics and Single Cover</p>
+            </div>
+        """
+    )
+
+    with gr.Row():
+    
+        # Left column (lyrics generation)
+        with gr.Column():
+            with gr.Accordion("Step 1. Generate Lyrics"):
+              gr.Markdown("Enter the starting text and select genre to generate lyrics")
+            with gr.Row():
+              input_start_text = gr.Textbox(placeholder='I am', label="Starting Text")
+              input_lyrics_type = gr.Radio(choices=['pop', 'rap', 'country', 'rock', 'r&b'], value='pop', label="Lyrics Genre")
+            button_gen_lyrics = gr.Button("Generate Lyrics", variant="primary")
+            output_generated_lyrics = gr.Textbox(label="Generated Lyrics", lines=8)
+
+        # Right column (single cover generation)
+        with gr.Column():
+          with gr.Accordion("Step 2. Generate Single Cover"):
+            gr.Markdown("Cover will be generated based on style, effect and generated lyrics")
+          with gr.Row():
+            input_cover_style = gr.Dropdown(choices=['painted', 'abstract', 'minimalist', 'illustrated', 'photographic', 'vintage'], value='painted', label="Track Cover Style")
+            input_cover_effect = gr.Radio(choices=['black and white', 'highly detailed', 'blurred'], value='highly detailed', label="Track Cover Effect")
+          button_gen_cover = gr.Button("Generate Cover", variant="primary")
+          output_generated_cover = gr.Image(label="Generated Cover")
+            
+    # Bind functions to buttons
+    button_gen_lyrics.click(fn=generate_lyrics, inputs=[input_lyrics_type , input_start_text], outputs=output_generated_lyrics)
+    button_gen_cover.click(fn=generate_cover, inputs=[output_generated_lyrics, input_cover_style, input_cover_effect], outputs=output_generated_cover)
+
+demo.launch(debug=True)

requirements.txt

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+transformers
+torch
+sentencepiece
+diffusers[torch]
+accelerate
+scipy