Update app.py
Browse files
app.py
CHANGED
|
@@ -6,59 +6,76 @@ from keybert import KeyBERT
|
|
| 6 |
import numpy as np
|
| 7 |
import os
|
| 8 |
|
| 9 |
-
# Load models
|
| 10 |
whisper_model = whisper.load_model("base")
|
| 11 |
kw_model = KeyBERT()
|
| 12 |
|
|
|
|
|
|
|
|
|
|
| 13 |
def process_video(video_path, caption="Your Caption"):
|
| 14 |
-
# Load video
|
| 15 |
clip = VideoFileClip(video_path)
|
| 16 |
|
| 17 |
-
# Extract
|
| 18 |
frame = clip.get_frame(5)
|
| 19 |
image = Image.fromarray(np.uint8(frame))
|
| 20 |
draw = ImageDraw.Draw(image)
|
| 21 |
-
|
| 22 |
-
|
| 23 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 24 |
thumbnail_path = "thumbnail.jpg"
|
| 25 |
image.save(thumbnail_path)
|
| 26 |
|
| 27 |
-
# Transcribe Hindi
|
| 28 |
result = whisper_model.transcribe(video_path, language="hi")
|
| 29 |
text = result["text"]
|
| 30 |
|
| 31 |
-
# Extract keywords
|
| 32 |
keywords = kw_model.extract_keywords(text, keyphrase_ngram_range=(1, 2), stop_words='english')
|
| 33 |
keywords_list = [kw[0] for kw in keywords]
|
| 34 |
|
| 35 |
-
# Burn caption
|
| 36 |
-
|
| 37 |
-
|
| 38 |
-
|
| 39 |
-
|
| 40 |
-
|
| 41 |
-
|
| 42 |
-
|
| 43 |
-
|
| 44 |
-
|
| 45 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 46 |
|
| 47 |
-
|
| 48 |
output_path = "output_with_caption.mp4"
|
| 49 |
-
final.write_videofile(output_path, codec=
|
| 50 |
|
| 51 |
return thumbnail_path, ", ".join(keywords_list), output_path
|
| 52 |
|
| 53 |
# Gradio UI
|
| 54 |
with gr.Blocks() as demo:
|
| 55 |
-
gr.Markdown("# Video Thumbnail
|
| 56 |
-
video_input = gr.File(label="Upload Video", type="filepath")
|
| 57 |
-
caption_input = gr.Textbox(label="
|
| 58 |
-
generate_button = gr.Button("Generate Thumbnail &
|
| 59 |
-
thumbnail_output = gr.Image(label="Generated Thumbnail")
|
| 60 |
-
keywords_output = gr.Textbox(label="SEO Keywords")
|
| 61 |
-
video_output = gr.File(label="Download
|
| 62 |
|
| 63 |
generate_button.click(
|
| 64 |
fn=process_video,
|
|
@@ -66,4 +83,4 @@ with gr.Blocks() as demo:
|
|
| 66 |
outputs=[thumbnail_output, keywords_output, video_output]
|
| 67 |
)
|
| 68 |
|
| 69 |
-
demo.launch()
|
|
|
|
| 6 |
import numpy as np
|
| 7 |
import os
|
| 8 |
|
| 9 |
+
# Load Whisper and KeyBERT models
|
| 10 |
whisper_model = whisper.load_model("base")
|
| 11 |
kw_model = KeyBERT()
|
| 12 |
|
| 13 |
+
# Path to Hindi-supporting font (adjust if needed)
|
| 14 |
+
FONT_PATH = "/usr/share/fonts/truetype/noto/NotoSansDevanagari-Regular.ttf" # Use system font or bundle locally
|
| 15 |
+
|
| 16 |
def process_video(video_path, caption="Your Caption"):
|
| 17 |
+
# Load the video
|
| 18 |
clip = VideoFileClip(video_path)
|
| 19 |
|
| 20 |
+
# Extract frame at 5 seconds
|
| 21 |
frame = clip.get_frame(5)
|
| 22 |
image = Image.fromarray(np.uint8(frame))
|
| 23 |
draw = ImageDraw.Draw(image)
|
| 24 |
+
|
| 25 |
+
# Load PIL font (for thumbnail)
|
| 26 |
+
try:
|
| 27 |
+
font = ImageFont.truetype(FONT_PATH, size=40)
|
| 28 |
+
except:
|
| 29 |
+
font = ImageFont.load_default()
|
| 30 |
+
|
| 31 |
+
draw.text((50, image.height - 100), caption, fill="white", font=font)
|
| 32 |
+
|
| 33 |
thumbnail_path = "thumbnail.jpg"
|
| 34 |
image.save(thumbnail_path)
|
| 35 |
|
| 36 |
+
# Transcribe audio with Whisper in Hindi
|
| 37 |
result = whisper_model.transcribe(video_path, language="hi")
|
| 38 |
text = result["text"]
|
| 39 |
|
| 40 |
+
# Extract keywords using KeyBERT
|
| 41 |
keywords = kw_model.extract_keywords(text, keyphrase_ngram_range=(1, 2), stop_words='english')
|
| 42 |
keywords_list = [kw[0] for kw in keywords]
|
| 43 |
|
| 44 |
+
# Burn caption onto video
|
| 45 |
+
try:
|
| 46 |
+
text_clip = TextClip(
|
| 47 |
+
caption,
|
| 48 |
+
fontsize=50,
|
| 49 |
+
color='white',
|
| 50 |
+
font=FONT_PATH,
|
| 51 |
+
method='caption',
|
| 52 |
+
size=(clip.w, None)
|
| 53 |
+
).set_position(("center", "bottom")).set_duration(clip.duration)
|
| 54 |
+
except:
|
| 55 |
+
# fallback in case font doesn't support Hindi
|
| 56 |
+
text_clip = TextClip(
|
| 57 |
+
caption,
|
| 58 |
+
fontsize=50,
|
| 59 |
+
color='white',
|
| 60 |
+
method='caption',
|
| 61 |
+
size=(clip.w, None)
|
| 62 |
+
).set_position(("center", "bottom")).set_duration(clip.duration)
|
| 63 |
|
| 64 |
+
final = CompositeVideoClip([clip, text_clip])
|
| 65 |
output_path = "output_with_caption.mp4"
|
| 66 |
+
final.write_videofile(output_path, codec="libx264", audio_codec="aac")
|
| 67 |
|
| 68 |
return thumbnail_path, ", ".join(keywords_list), output_path
|
| 69 |
|
| 70 |
# Gradio UI
|
| 71 |
with gr.Blocks() as demo:
|
| 72 |
+
gr.Markdown("# 📹 Video Thumbnail & SEO Tool (Hindi Supported)")
|
| 73 |
+
video_input = gr.File(label="📁 Upload Video", type="filepath")
|
| 74 |
+
caption_input = gr.Textbox(label="📝 Caption for Thumbnail/Video", value="यह शानदार वीडियो है!")
|
| 75 |
+
generate_button = gr.Button("🚀 Generate Thumbnail, SEO & Video")
|
| 76 |
+
thumbnail_output = gr.Image(label="🖼️ Generated Thumbnail")
|
| 77 |
+
keywords_output = gr.Textbox(label="🔑 Extracted SEO Keywords")
|
| 78 |
+
video_output = gr.File(label="⬇️ Download Final Video")
|
| 79 |
|
| 80 |
generate_button.click(
|
| 81 |
fn=process_video,
|
|
|
|
| 83 |
outputs=[thumbnail_output, keywords_output, video_output]
|
| 84 |
)
|
| 85 |
|
| 86 |
+
demo.launch(share=True) # share=True creates public link
|