Upload app.py

app.py

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+# -*- coding: utf-8 -*-
+"""Untitled1.ipynb
+
+Automatically generated by Colaboratory.
+
+Original file is located at
+    https://colab.research.google.com/drive/1yIRyQq7IUIqBQiXAPKoa0n2gT8Lr_qMw
+"""
+
+!pip install openai
+!pip install imageio
+!pip install replicate
+!pip install gradio
+
+"""## Importing Libraries"""
+
+import openai
+import re
+import pandas as pd
+import replicate
+import pandas as pd
+from PIL import Image
+import requests
+from io import BytesIO
+import os
+from IPython.display import Audio, display
+import gradio as gr
+import numpy
+from PIL import ImageDraw
+from PIL import ImageFont
+import random
+
+!git clone https://github.com/Neelanjan-chakraborty/MelodyGen.git
+
+!ls MelodyGen
+
+"""## Function To Generate Genre Based on Mood"""
+
+def generate_genre_recommendations(mood,key):
+    openai.api_key=key
+    response = openai.Completion.create(
+        engine='text-davinci-003',
+        prompt=f"I'm feeling {mood} and I want only genre recommendations and not songs also please separate using comma.",
+        max_tokens=100,
+        n=1,
+        stop=None,
+        temperature=0.5
+    )
+
+    genres = set(response.choices[0].text.strip().split(','))  # Extract genres from response
+
+    #if len(genres) < 3:
+    #    # Provide some default genre recommendations
+    #    genres = {'Pop', 'Rock', 'Electronic'}
+
+    genre_recommendations = list(genres)[:3]  # Limit to 3 unique genres
+
+    return ', '.join(genre_recommendations)  # Return as comma-separated string
+
+def recommend(user_mood,key):
+  genre_recommendations = generate_genre_recommendations(user_mood,key)
+  out = genre_recommendations.split(',')
+  return out
+
+"""## Function to Generate Melody"""
+
+def melodygen(api_token,prompt):
+  client = replicate.Client(api_token)
+  output = client.run(
+      "joehoover/musicgen:ba9bdc5a86f60525ba23590a03ae1e407b9a40f4a318a85af85748d641e6659f",
+      input={"model_version": "melody","prompt":prompt,"continuation_start": 0,"continuation_end": 30, "duration":30,
+      }
+  )
+  return output
+
+#api_token='r8_Z30IhmLhqMoeJeNkl4S92JzSp8stlh82NZAnI'
+#prompt=input("Enter your Genre : ")
+#melodygen(api_token,prompt)
+
+"""## Function To Generate a Song Name"""
+
+def generate_song_name(mood,key):
+  openai.api_key=key
+  response = openai.Completion.create(
+      engine='text-davinci-003',
+      prompt=f"I'm feeling {mood} and I want only random ai generated Song Name and please separate these names using comma.",
+      max_tokens=100,
+      n=1,
+      stop=None,
+      temperature=0.5
+  )
+
+  names = set(response.choices[0].text.strip().split(','))  # Extract genres from response
+  get_names = list(names)[:3]  # Limit to 3 unique genres
+  return ', '.join(get_names)  # Return as comma-separated string(mood):
+
+"""## Function To Generate Album Art and Album Art Animation"""
+
+def albumart(user_mood,key,name):
+  openai.api_key=key
+  response = openai.Image.create(
+    prompt=f"Music album art of mood{user_mood}",
+    n=1,
+    size="512x512"
+  )
+  image_url = response['data'][0]['url']
+  # Fetch the image from the URL
+  response = requests.get(image_url)
+  response.raise_for_status()
+  # Load the image into a PIL Image object
+  image = Image.open(BytesIO(response.content))
+  # Load the font
+  font_path = "MelodyGen/Lobster-Regular.ttf"
+  font_size = 48
+  font = ImageFont.truetype(font_path, font_size)
+  position = (image.width // 2, image.height // 2)
+  # Create a new ImageDraw object
+  draw = ImageDraw.Draw(image)
+  # Get a random color
+  color = (random.randint(0, 255), random.randint(0, 255), random.randint(0, 255))
+  # Calculate the position to center the text
+  text_width, text_height = draw.textsize(name, font=font)
+  text_position = (position[0] - text_width // 2, position[1] - text_height // 2)
+  # Add the text to the image
+  draw.text(text_position, name, font=font, fill=color)
+  path='album_art.jpg'
+  image.save(path)
+  return path
+
+def overlay_images(background_image_path, foreground_image_path):
+    # Open the background and foreground images
+    background_image = Image.open(background_image_path).resize((512, 512))
+    foreground_image = Image.open(foreground_image_path).resize((1024, 768)).convert("RGBA")
+
+    # Create a new image with transparency
+    final_image = Image.new("RGBA", (1024, 768))
+
+    # Calculate the position to paste the background image at the center
+    paste_x = int((1024 - background_image.width) / 2)
+    paste_y = int((768 - background_image.height) / 2)
+
+    # Overlay the background image at the center of the final image
+    final_image.paste(background_image, (paste_x, paste_y))
+
+    # Overlay the foreground image on the background image
+    final_image.paste(foreground_image, (0, 0), mask=foreground_image)
+
+    # Convert the image mode to RGB (removing alpha channel)
+    final_image = final_image.convert("RGB")
+
+    # Return the final image
+    return final_image
+
+
+background_image_path = "/content/input.jpg"  # Path to the background image
+foreground_image_path = "/content/Transparent CD Case Mockup2.png"  # Path to the foreground PNG image
+
+result_image = overlay_images(background_image_path, foreground_image_path)
+
+result_image.save("result.jpg")  # Save the final image to a file
+result_image.show()  # Display the final image
+
+!pip install imageio
+
+from PIL import Image, ImageSequence
+
+def overlay_images(background_image_path, foreground_image_path, num_frames=36, rotation_angle=10):
+    # Open the background and foreground images
+    background_image = Image.open(background_image_path).resize((512, 512))
+    foreground_image = Image.open(foreground_image_path).resize((1024, 768)).convert("RGBA")
+
+    # Create a new image with transparency
+    final_image = Image.new("RGBA", (1024, 768))
+
+    # Calculate the position to paste the background image at the center
+    paste_x = int((1024 - background_image.width) / 2)
+    paste_y = int((768 - background_image.height) / 2)
+
+    # Create a list to store the frames of the GIF animation
+    frames = []
+
+    # Calculate the center point of the background image
+    center_x = int(background_image.width / 2)
+    center_y = int(background_image.height / 2)
+
+    # Rotate the background image and create frames for the GIF animation
+    for angle in range(0, 360, rotation_angle):
+        # Create a copy of the background image
+        rotated_image = background_image.copy()
+
+        # Rotate the image by the specified angle around its center
+        rotated_image = rotated_image.rotate(angle, resample=Image.BICUBIC, center=(center_x, center_y))
+
+        # Overlay the rotated background image at the center of the final image
+        final_image.paste(rotated_image, (paste_x, paste_y))
+
+        # Overlay the foreground image on the background image
+        final_image.paste(foreground_image, (0, 0), mask=foreground_image)
+
+        # Append the current frame to the list of frames
+        frames.append(final_image.copy())
+
+    # Convert the image mode of frames to RGB (removing alpha channel)
+    frames_rgb = [frame.convert("RGB") for frame in frames]
+
+    # Save the frames as an animated GIF
+    output_path = "animation.gif"
+    frames_rgb[0].save(output_path, save_all=True, append_images=frames_rgb[1:], loop=0, duration=100,optimize=True, quality=100)
+
+    # Return the output path of the animated GIF
+    return output_path
+
+
+
+
+#background_image_path = "/content/input.png"  # Path to the background image
+#foreground_image_path = "/content/Transparent CD Case Mockup2.png"  # Path to the foreground PNG image
+#rotation_angle = 10
+
+#overlay_images(background_image_path, foreground_image_path)
+
+from PIL import Image, ImageSequence
+def overlay_images(background_image_path):
+    foreground_image_path='MelodyGen/Mockup4.png'
+    num_frames=36
+    rotation_angle=10
+    # Open the background and foreground images
+    background_image = Image.open(background_image_path).resize((600, 600))
+    foreground_image = Image.open(foreground_image_path).resize((1024, 768)).convert("RGBA")
+
+    # Create a new image with transparency
+    final_image = Image.new("RGBA", (1024, 768))
+
+    # Calculate the position to paste the background image at the center
+    paste_x = int(100.50)
+    paste_y = int(100.50)
+
+    # Create a list to store the frames of the GIF animation
+    frames = []
+
+    # Calculate the center point of the background image
+    center_x = int(background_image.width / 2)
+    center_y = int(background_image.height / 2)
+
+    # Rotate the background image and create frames for the GIF animation
+    for angle in range(0, 360, rotation_angle):
+        # Create a copy of the background image
+        rotated_image = background_image.copy()
+
+        # Rotate the image by the specified angle around its center
+        rotated_image = rotated_image.rotate(angle, resample=Image.BICUBIC, center=(center_x, center_y))
+
+        # Overlay the rotated background image at the center of the final image
+        final_image.paste(rotated_image, (paste_x, paste_y))
+
+        # Overlay the foreground image on the background image
+        final_image.paste(foreground_image, (0, 0), mask=foreground_image)
+
+        # Append the current frame to the list of frames
+        frames.append(final_image.copy())
+
+    # Convert the image mode of frames to RGB (removing alpha channel)
+    frames_rgb = [frame.convert("RGB") for frame in frames]
+
+    # Save the frames as an animated GIF
+    output_path = "animation2.gif"
+    frames_rgb[0].save(output_path, save_all=True, append_images=frames_rgb[1:], loop=0, duration=100,optimize=True, quality=100)
+
+    # Return the output path of the animated GIF
+    return output_path
+
+
+
+
+#background_image_path = "/content/input.png"  # Path to the background image
+#foreground_image_path = "/content/Mockup4.png"  # Path to the foreground PNG image
+#rotation_angle = 10
+
+#overlay_images(background_image_path, foreground_image_path)
+
+def main_func(user_mood,key,api_token,genre):
+  if genre is None:
+      out = recommend(user_mood, key)[0]
+  else:
+      out = genre
+  name=generate_song_name(user_mood,key).split(",")
+  image=albumart(user_mood ,key,name[0])
+  album_art=overlay_images(image)
+  song=melodygen(api_token,out[0])
+
+  return album_art,name[0],genre,song
+
+
+"""## Gradio UI"""
+
+css1= """.gradio-container{
+	background: linear-gradient(-45deg, #ee7752, #e73c7e, #23a6d5, #23d5ab);
+	background-size: 400% 400%;
+	animation: gradient 15s ease infinite;
+	height: 100vh;
+}
+
+@keyframes gradient {
+	0% {
+		background-position: 0% 50%;
+	}
+	50% {
+		background-position: 100% 50%;
+	}
+	100% {
+		background-position: 0% 50%;
+	}
+}
+.mood {
+background: linear-gradient(-45deg, #ee7752, #e73c7e, #23a6d5, #23d5ab);
+	background-size: 400% 400%;
+	animation: gradient 15s ease infinite;
+	height: 100vh;
+}
+
+@keyframes gradient {
+	0% {
+		background-position: 0% 50%;
+	}
+	50% {
+		background-position: 100% 50%;
+	}
+	100% {
+		background-position: 0% 50%;
+	}
+}
+.OpenAI {
+background: linear-gradient(-45deg, #ee7752, #e73c7e, #23a6d5, #23d5ab)!important;
+	animation: gradient 15s ease infinite!important;
+}
+
+@keyframes gradient {
+	0% {
+		background-position: 0% 50%;
+	}
+	50% {
+		background-position: 100% 50%;
+	}
+	100% {
+		background-position: 0% 50%;
+	}
+}
+}
+"""
+
+def check_box(check,ch):
+  if(check==True):
+      return gr.Dropdown.update(visible=True)
+  return gr.Dropdown.update(visible=False, value=None)
+
+
+with gr.Blocks(css=css1,theme='freddyaboulton/dracula_revamped',title="🎵MoodMelody🤖 by Neelanjan",thumbnail="MelodyGen/Mood-Melody.jpg") as demo:
+  with gr.Row():
+    with gr.Column(scale=1):
+      Mood=textbox = gr.Textbox(label="Enter Your Mood",value="Happy",placeholder="How is Your Mood Now?", elem_id="warning", elem_classes="feedback")
+      Key=textbox = gr.Textbox(label="Enter Open AI Key",placeholder="sk-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx",elem_id="warning", elem_classes="feedback")
+      Key2=textbox = gr.Textbox(label="Enter Replicate Key",placeholder="r8-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx",elem_id="warning", elem_classes="feedback")
+      check=gr.Checkbox(label="Custom Genre?", info="Select if you want custom Genres",value=True,elem_id="warning", elem_classes="feedback")
+      ch=gr.Dropdown(
+          [
+              "Acoustic","Alternative","Ambient","Blues","Classical","Country","Dance","Disco","Electronic","Folk","Funk","Gospel","Hip Hop","Indie","Jazz","Latin","Metal","Opera","Pop","Punk",
+              "R&B","Reggae","Rock","Soul","Techno","World",# Add more genres as needed
+          ],max_choices=1,
+          multiselect=True,visible=True,
+          label="Music Genres",
+          info="Select  only one  genre of music"
+      )
+
+      check.change(check_box, check, ch)
+      btn = gr.Button(value="Generate Song")
+    with gr.Column(scale=4):
+      SongName=gr.Textbox(label="Song Name",placeholder="Song Name will appear Here")
+      Genres=gr.Textbox(label="Genre",placeholder="Genres")
+      AlbumArt=gr.Image(label="AI Generated Album Art")
+      MusicGen=gr.Audio(label="AI Generated Music",format="wav")
+
+
+
+    btn.click(main_func, inputs=[Mood,Key,Key2,ch], outputs=[AlbumArt,SongName,Genres,MusicGen])
+
+if __name__ == "__main__":
+   demo.launch(share=True,show_error=True,debug=True)