Create app.py

app.py

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+import gradio as gr
+from moviepy.editor import VideoFileClip
+from PIL import Image, ImageDraw, ImageFont
+import whisper
+from keybert import KeyBERT
+import numpy as np
+
+# Load Whisper model and KeyBERT model
+whisper_model = whisper.load_model("base")
+kw_model = KeyBERT()
+
+def process_video(video_path, caption="Your Caption"):
+    # Extract frame at 5 seconds
+    clip = VideoFileClip(video_path)
+    frame = clip.get_frame(5)  # 5 seconds
+    image = Image.fromarray(np.uint8(frame))
+
+    # Add caption
+    draw = ImageDraw.Draw(image)
+    font = ImageFont.truetype("arial.ttf", 40)  # Make sure Arial.ttf is available
+    text_position = (50, image.height - 100)
+    draw.text(text_position, caption, (255, 255, 255), font=font)
+
+    thumbnail_path = "thumbnail.jpg"
+    image.save(thumbnail_path)
+
+    # Extract keywords
+    result = whisper_model.transcribe(video_path)
+    text = result["text"]
+    keywords = kw_model.extract_keywords(text, keyphrase_ngram_range=(1, 2), stop_words='english')
+    keywords_list = [kw[0] for kw in keywords]
+
+    return thumbnail_path, ", ".join(keywords_list)
+
+# Gradio UI
+with gr.Blocks() as demo:
+    gr.Markdown("# Video Thumbnail Generator with SEO Keywords")
+    video_input = gr.File(label="Upload Video", type="filepath")
+    caption_input = gr.Textbox(label="Enter Caption for Thumbnail", value="Awesome Video!")
+    generate_button = gr.Button("Generate Thumbnail & Keywords")
+    thumbnail_output = gr.Image(label="Generated Thumbnail")
+    keywords_output = gr.Textbox(label="SEO Keywords")
+
+    generate_button.click(process_video, inputs=[video_input, caption_input], outputs=[thumbnail_output, keywords_output])
+
+# Launch in Hugging Face Spaces
+demo.launch()