diff --git a/.gitattributes b/.gitattributes
index a6344aac8c09253b3b630fb776ae94478aa0275b..e2d9729aae670eb88273b99ec1e813b08ea59162 100644
--- a/.gitattributes
+++ b/.gitattributes
@@ -33,3 +33,5 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
*.zip filter=lfs diff=lfs merge=lfs -text
*.zst filter=lfs diff=lfs merge=lfs -text
*tfevents* filter=lfs diff=lfs merge=lfs -text
+*.png filter=lfs diff=lfs merge=lfs -text
+*.mp4 filter=lfs diff=lfs merge=lfs -text
diff --git a/LICENSE b/LICENSE
new file mode 100644
index 0000000000000000000000000000000000000000..a27ca3f82e8814609adedf4bfae2d1146d13e4ea
--- /dev/null
+++ b/LICENSE
@@ -0,0 +1,77 @@
+TENCENT HUNYUAN COMMUNITY LICENSE AGREEMENT
+Tencent HunyuanVideo-Foley Release Date: August 28, 2025
+THIS LICENSE AGREEMENT DOES NOT APPLY IN THE EUROPEAN UNION, UNITED KINGDOM AND SOUTH KOREA AND IS EXPRESSLY LIMITED TO THE TERRITORY, AS DEFINED BELOW.
+By clicking to agree or by using, reproducing, modifying, distributing, performing or displaying any portion or element of the Tencent Hunyuan Works, including via any Hosted Service, You will be deemed to have recognized and accepted the content of this Agreement, which is effective immediately.
+1. DEFINITIONS.
+a. “Acceptable Use Policy” shall mean the policy made available by Tencent as set forth in the Exhibit A.
+b. “Agreement” shall mean the terms and conditions for use, reproduction, distribution, modification, performance and displaying of Tencent Hunyuan Works or any portion or element thereof set forth herein.
+c. “Documentation” shall mean the specifications, manuals and documentation for Tencent Hunyuan made publicly available by Tencent.
+d. “Hosted Service” shall mean a hosted service offered via an application programming interface (API), web access, or any other electronic or remote means.
+e. “Licensee,” “You” or “Your” shall mean a natural person or legal entity exercising the rights granted by this Agreement and/or using the Tencent Hunyuan Works for any purpose and in any field of use.
+f. “Materials” shall mean, collectively, Tencent’s proprietary Tencent Hunyuan and Documentation (and any portion thereof) as made available by Tencent under this Agreement.
+g. “Model Derivatives” shall mean all: (i) modifications to Tencent Hunyuan or any Model Derivative of Tencent Hunyuan; (ii) works based on Tencent Hunyuan or any Model Derivative of Tencent Hunyuan; or (iii) any other machine learning model which is created by transfer of patterns of the weights, parameters, operations, or Output of Tencent Hunyuan or any Model Derivative of Tencent Hunyuan, to that model in order to cause that model to perform similarly to Tencent Hunyuan or a Model Derivative of Tencent Hunyuan, including distillation methods, methods that use intermediate data representations, or methods based on the generation of synthetic data Outputs by Tencent Hunyuan or a Model Derivative of Tencent Hunyuan for training that model. For clarity, Outputs by themselves are not deemed Model Derivatives.
+h. “Output” shall mean the information and/or content output of Tencent Hunyuan or a Model Derivative that results from operating or otherwise using Tencent Hunyuan or a Model Derivative, including via a Hosted Service.
+i. “Tencent,” “We” or “Us” shall mean the applicable entity or entities in the Tencent corporate family that own(s) intellectual property or other rights embodied in or utilized by the Materials.
+j. “Tencent Hunyuan” shall mean the large language models, text/image/video/audio/3D generation models, and multimodal large language models and their software and algorithms, including trained model weights, parameters (including optimizer states), machine-learning model code, inference-enabling code, training-enabling code, fine-tuning enabling code and other elements of the foregoing made publicly available by Us, including, without limitation to, Tencent HunyuanVideo-Foley released at [https://github.com/Tencent-Hunyuan/HunyuanVideo-Foley].
+k. “Tencent Hunyuan Works” shall mean: (i) the Materials; (ii) Model Derivatives; and (iii) all derivative works thereof.
+l. “Territory” shall mean the worldwide territory, excluding the territory of the European Union, United Kingdom and South Korea.
+m. “Third Party” or “Third Parties” shall mean individuals or legal entities that are not under common control with Us or You.
+n. “including” shall mean including but not limited to.
+2. GRANT OF RIGHTS.
+We grant You, for the Territory only, a non-exclusive, non-transferable and royalty-free limited license under Tencent’s intellectual property or other rights owned by Us embodied in or utilized by the Materials to use, reproduce, distribute, create derivative works of (including Model Derivatives), and make modifications to the Materials, only in accordance with the terms of this Agreement and the Acceptable Use Policy, and You must not violate (or encourage or permit anyone else to violate) any term of this Agreement or the Acceptable Use Policy.
+3. DISTRIBUTION.
+You may, subject to Your compliance with this Agreement, distribute or make available to Third Parties the Tencent Hunyuan Works, exclusively in the Territory, provided that You meet all of the following conditions:
+a. You must provide all such Third Party recipients of the Tencent Hunyuan Works or products or services using them a copy of this Agreement;
+b. You must cause any modified files to carry prominent notices stating that You changed the files;
+c. You are encouraged to: (i) publish at least one technology introduction blogpost or one public statement expressing Your experience of using the Tencent Hunyuan Works; and (ii) mark the products or services developed by using the Tencent Hunyuan Works to indicate that the product/service is “Powered by Tencent Hunyuan”; and
+d. All distributions to Third Parties (other than through a Hosted Service) must be accompanied by a “Notice” text file that contains the following notice: “Tencent Hunyuan is licensed under the Tencent Hunyuan Community License Agreement, Copyright © 2025 Tencent. All Rights Reserved. The trademark rights of “Tencent Hunyuan” are owned by Tencent or its affiliate.”
+You may add Your own copyright statement to Your modifications and, except as set forth in this Section and in Section 5, may provide additional or different license terms and conditions for use, reproduction, or distribution of Your modifications, or for any such Model Derivatives as a whole, provided Your use, reproduction, modification, distribution, performance and display of the work otherwise complies with the terms and conditions of this Agreement (including as regards the Territory). If You receive Tencent Hunyuan Works from a Licensee as part of an integrated end user product, then this Section 3 of this Agreement will not apply to You.
+4. ADDITIONAL COMMERCIAL TERMS.
+If, on the Tencent Hunyuan version release date, the monthly active users of all products or services made available by or for Licensee is greater than 100 million monthly active users in the preceding calendar month, You must request a license from Tencent, which Tencent may grant to You in its sole discretion, and You are not authorized to exercise any of the rights under this Agreement unless or until Tencent otherwise expressly grants You such rights.
+5. RULES OF USE.
+a. Your use of the Tencent Hunyuan Works must comply with applicable laws and regulations (including trade compliance laws and regulations) and adhere to the Acceptable Use Policy for the Tencent Hunyuan Works, which is hereby incorporated by reference into this Agreement. You must include the use restrictions referenced in these Sections 5(a) and 5(b) as an enforceable provision in any agreement (e.g., license agreement, terms of use, etc.) governing the use and/or distribution of Tencent Hunyuan Works and You must provide notice to subsequent users to whom You distribute that Tencent Hunyuan Works are subject to the use restrictions in these Sections 5(a) and 5(b).
+b. You must not use the Tencent Hunyuan Works or any Output or results of the Tencent Hunyuan Works to improve any other AI model (other than Tencent Hunyuan or Model Derivatives thereof).
+c. You must not use, reproduce, modify, distribute, or display the Tencent Hunyuan Works, Output or results of the Tencent Hunyuan Works outside the Territory. Any such use outside the Territory is unlicensed and unauthorized under this Agreement.
+6. INTELLECTUAL PROPERTY.
+a. Subject to Tencent’s ownership of Tencent Hunyuan Works made by or for Tencent and intellectual property rights therein, conditioned upon Your compliance with the terms and conditions of this Agreement, as between You and Tencent, You will be the owner of any derivative works and modifications of the Materials and any Model Derivatives that are made by or for You.
+b. No trademark licenses are granted under this Agreement, and in connection with the Tencent Hunyuan Works, Licensee may not use any name or mark owned by or associated with Tencent or any of its affiliates, except as required for reasonable and customary use in describing and distributing the Tencent Hunyuan Works. Tencent hereby grants You a license to use “Tencent Hunyuan” (the “Mark”) in the Territory solely as required to comply with the provisions of Section 3(c), provided that You comply with any applicable laws related to trademark protection. All goodwill arising out of Your use of the Mark will inure to the benefit of Tencent.
+c. If You commence a lawsuit or other proceedings (including a cross-claim or counterclaim in a lawsuit) against Us or any person or entity alleging that the Materials or any Output, or any portion of any of the foregoing, infringe any intellectual property or other right owned or licensable by You, then all licenses granted to You under this Agreement shall terminate as of the date such lawsuit or other proceeding is filed. You will defend, indemnify and hold harmless Us from and against any claim by any Third Party arising out of or related to Your or the Third Party’s use or distribution of the Tencent Hunyuan Works.
+d. Tencent claims no rights in Outputs You generate. You and Your users are solely responsible for Outputs and their subsequent uses.
+7. DISCLAIMERS OF WARRANTY AND LIMITATIONS OF LIABILITY.
+a. We are not obligated to support, update, provide training for, or develop any further version of the Tencent Hunyuan Works or to grant any license thereto.
+b. UNLESS AND ONLY TO THE EXTENT REQUIRED BY APPLICABLE LAW, THE TENCENT HUNYUAN WORKS AND ANY OUTPUT AND RESULTS THEREFROM ARE PROVIDED “AS IS” WITHOUT ANY EXPRESS OR IMPLIED WARRANTIES OF ANY KIND INCLUDING ANY WARRANTIES OF TITLE, MERCHANTABILITY, NONINFRINGEMENT, COURSE OF DEALING, USAGE OF TRADE, OR FITNESS FOR A PARTICULAR PURPOSE. YOU ARE SOLELY RESPONSIBLE FOR DETERMINING THE APPROPRIATENESS OF USING, REPRODUCING, MODIFYING, PERFORMING, DISPLAYING OR DISTRIBUTING ANY OF THE TENCENT HUNYUAN WORKS OR OUTPUTS AND ASSUME ANY AND ALL RISKS ASSOCIATED WITH YOUR OR A THIRD PARTY’S USE OR DISTRIBUTION OF ANY OF THE TENCENT HUNYUAN WORKS OR OUTPUTS AND YOUR EXERCISE OF RIGHTS AND PERMISSIONS UNDER THIS AGREEMENT.
+c. TO THE FULLEST EXTENT PERMITTED BY APPLICABLE LAW, IN NO EVENT SHALL TENCENT OR ITS AFFILIATES BE LIABLE UNDER ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, TORT, NEGLIGENCE, PRODUCTS LIABILITY, OR OTHERWISE, FOR ANY DAMAGES, INCLUDING ANY DIRECT, INDIRECT, SPECIAL, INCIDENTAL, EXEMPLARY, CONSEQUENTIAL OR PUNITIVE DAMAGES, OR LOST PROFITS OF ANY KIND ARISING FROM THIS AGREEMENT OR RELATED TO ANY OF THE TENCENT HUNYUAN WORKS OR OUTPUTS, EVEN IF TENCENT OR ITS AFFILIATES HAVE BEEN ADVISED OF THE POSSIBILITY OF ANY OF THE FOREGOING.
+8. SURVIVAL AND TERMINATION.
+a. The term of this Agreement shall commence upon Your acceptance of this Agreement or access to the Materials and will continue in full force and effect until terminated in accordance with the terms and conditions herein.
+b. We may terminate this Agreement if You breach any of the terms or conditions of this Agreement. Upon termination of this Agreement, You must promptly delete and cease use of the Tencent Hunyuan Works. Sections 6(a), 6(c), 7 and 9 shall survive the termination of this Agreement.
+9. GOVERNING LAW AND JURISDICTION.
+a. This Agreement and any dispute arising out of or relating to it will be governed by the laws of the Hong Kong Special Administrative Region of the People’s Republic of China, without regard to conflict of law principles, and the UN Convention on Contracts for the International Sale of Goods does not apply to this Agreement.
+b. Exclusive jurisdiction and venue for any dispute arising out of or relating to this Agreement will be a court of competent jurisdiction in the Hong Kong Special Administrative Region of the People’s Republic of China, and Tencent and Licensee consent to the exclusive jurisdiction of such court with respect to any such dispute.
+
+EXHIBIT A
+ACCEPTABLE USE POLICY
+
+Tencent reserves the right to update this Acceptable Use Policy from time to time.
+Last modified: November 5, 2024
+
+Tencent endeavors to promote safe and fair use of its tools and features, including Tencent Hunyuan. You agree not to use Tencent Hunyuan or Model Derivatives:
+1. Outside the Territory;
+2. In any way that violates any applicable national, federal, state, local, international or any other law or regulation;
+3. To harm Yourself or others;
+4. To repurpose or distribute output from Tencent Hunyuan or any Model Derivatives to harm Yourself or others;
+5. To override or circumvent the safety guardrails and safeguards We have put in place;
+6. For the purpose of exploiting, harming or attempting to exploit or harm minors in any way;
+7. To generate or disseminate verifiably false information and/or content with the purpose of harming others or influencing elections;
+8. To generate or facilitate false online engagement, including fake reviews and other means of fake online engagement;
+9. To intentionally defame, disparage or otherwise harass others;
+10. To generate and/or disseminate malware (including ransomware) or any other content to be used for the purpose of harming electronic systems;
+11. To generate or disseminate personal identifiable information with the purpose of harming others;
+12. To generate or disseminate information (including images, code, posts, articles), and place the information in any public context (including –through the use of bot generated tweets), without expressly and conspicuously identifying that the information and/or content is machine generated;
+13. To impersonate another individual without consent, authorization, or legal right;
+14. To make high-stakes automated decisions in domains that affect an individual’s safety, rights or wellbeing (e.g., law enforcement, migration, medicine/health, management of critical infrastructure, safety components of products, essential services, credit, employment, housing, education, social scoring, or insurance);
+15. In a manner that violates or disrespects the social ethics and moral standards of other countries or regions;
+16. To perform, facilitate, threaten, incite, plan, promote or encourage violent extremism or terrorism;
+17. For any use intended to discriminate against or harm individuals or groups based on protected characteristics or categories, online or offline social behavior or known or predicted personal or personality characteristics;
+18. To intentionally exploit any of the vulnerabilities of a specific group of persons based on their age, social, physical or mental characteristics, in order to materially distort the behavior of a person pertaining to that group in a manner that causes or is likely to cause that person or another person physical or psychological harm;
+19. For military purposes;
+20. To engage in the unauthorized or unlicensed practice of any profession including, but not limited to, financial, legal, medical/health, or other professional practices.
diff --git a/app.py b/app.py
new file mode 100644
index 0000000000000000000000000000000000000000..d6fd0c679f20b45a96043fe61293a5d0baf0e251
--- /dev/null
+++ b/app.py
@@ -0,0 +1,814 @@
+import os
+import tempfile
+import gradio as gr
+import torch
+import torchaudio
+from loguru import logger
+from typing import Optional, Tuple
+import random
+import numpy as np
+
+from hunyuanvideo_foley.utils.model_utils import load_model
+from hunyuanvideo_foley.utils.feature_utils import feature_process
+from hunyuanvideo_foley.utils.model_utils import denoise_process
+from hunyuanvideo_foley.utils.media_utils import merge_audio_video
+
+# Global variables for model storage
+model_dict = None
+cfg = None
+device = None
+
+# need to modify the model path
+MODEL_PATH = os.environ.get("HIFI_FOLEY_MODEL_PATH", "./pretrained_models/")
+CONFIG_PATH = "configs/hunyuanvideo-foley-xxl.yaml"
+
+def setup_device(device_str: str = "auto", gpu_id: int = 0) -> torch.device:
+ """Setup computing device"""
+ if device_str == "auto":
+ if torch.cuda.is_available():
+ device = torch.device(f"cuda:{gpu_id}")
+ logger.info(f"Using CUDA device: {device}")
+ elif torch.backends.mps.is_available():
+ device = torch.device("mps")
+ logger.info("Using MPS device")
+ else:
+ device = torch.device("cpu")
+ logger.info("Using CPU device")
+ else:
+ if device_str == "cuda":
+ device = torch.device(f"cuda:{gpu_id}")
+ else:
+ device = torch.device(device_str)
+ logger.info(f"Using specified device: {device}")
+
+ return device
+
+def auto_load_models() -> str:
+ """Automatically load preset models"""
+ global model_dict, cfg, device
+
+ try:
+ if not os.path.exists(MODEL_PATH):
+ return f"❌ Model file not found: {MODEL_PATH}"
+ if not os.path.exists(CONFIG_PATH):
+ return f"❌ Config file not found: {CONFIG_PATH}"
+
+ # Use GPU by default
+ device = setup_device("auto", 0)
+
+ # Load model
+ logger.info("Auto-loading model...")
+ logger.info(f"Model path: {MODEL_PATH}")
+ logger.info(f"Config path: {CONFIG_PATH}")
+
+ model_dict, cfg = load_model(MODEL_PATH, CONFIG_PATH, device)
+
+ logger.info("✅ Model loaded successfully!")
+ return "✅ Model loaded successfully!"
+
+ except Exception as e:
+ logger.error(f"Model loading failed: {str(e)}")
+ return f"❌ Model loading failed: {str(e)}"
+
+def infer_single_video(
+ video_file,
+ text_prompt: str,
+ guidance_scale: float = 4.5,
+ num_inference_steps: int = 50,
+ sample_nums: int = 1
+) -> Tuple[list, str]:
+ """Single video inference"""
+ global model_dict, cfg, device
+
+ if model_dict is None or cfg is None:
+ return [], "❌ Please load the model first!"
+
+ if video_file is None:
+ return [], "❌ Please upload a video file!"
+
+ # Allow empty text prompt, use empty string if no prompt provided
+ if text_prompt is None:
+ text_prompt = ""
+ text_prompt = text_prompt.strip()
+
+ try:
+ logger.info(f"Processing video: {video_file}")
+ logger.info(f"Text prompt: {text_prompt}")
+
+ # Feature processing
+ visual_feats, text_feats, audio_len_in_s = feature_process(
+ video_file,
+ text_prompt,
+ model_dict,
+ cfg
+ )
+
+ # Denoising process to generate multiple audio samples
+ # Note: The model now generates sample_nums audio samples per inference
+ # The denoise_process function returns audio with shape [batch_size, channels, samples]
+ logger.info(f"Generating {sample_nums} audio samples...")
+ audio, sample_rate = denoise_process(
+ visual_feats,
+ text_feats,
+ audio_len_in_s,
+ model_dict,
+ cfg,
+ guidance_scale=guidance_scale,
+ num_inference_steps=num_inference_steps,
+ batch_size=sample_nums
+ )
+
+ # Create temporary files to save results
+ temp_dir = tempfile.mkdtemp()
+ video_outputs = []
+
+ # Process each generated audio sample
+ for i in range(sample_nums):
+ # Save audio file
+ audio_output = os.path.join(temp_dir, f"generated_audio_{i+1}.wav")
+ torchaudio.save(audio_output, audio[i], sample_rate)
+
+ # Merge video and audio
+ video_output = os.path.join(temp_dir, f"video_with_audio_{i+1}.mp4")
+ merge_audio_video(audio_output, video_file, video_output)
+ video_outputs.append(video_output)
+
+ logger.info(f"Inference completed! Generated {sample_nums} samples.")
+ return video_outputs, f"✅ Generated {sample_nums} audio sample(s) successfully!"
+
+ except Exception as e:
+ logger.error(f"Inference failed: {str(e)}")
+ return [], f"❌ Inference failed: {str(e)}"
+
+def update_video_outputs(video_list, status_msg):
+ """Update video outputs based on the number of generated samples"""
+ # Initialize all outputs as None
+ outputs = [None] * 6
+
+ # Set values based on generated videos
+ for i, video_path in enumerate(video_list[:6]): # Max 6 samples
+ outputs[i] = video_path
+
+ # Return all outputs plus status message
+ return tuple(outputs + [status_msg])
+
+def create_gradio_interface():
+ """Create Gradio interface"""
+
+ # Custom CSS for beautiful interface with better contrast
+ css = """
+ .gradio-container {
+ font-family: 'Inter', -apple-system, BlinkMacSystemFont, 'Segoe UI', sans-serif;
+ background: linear-gradient(135deg, #f5f7fa 0%, #c3cfe2 100%);
+ min-height: 100vh;
+ }
+
+ .main-header {
+ text-align: center;
+ padding: 2rem 0;
+ background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
+ border-radius: 20px;
+ margin-bottom: 2rem;
+ box-shadow: 0 8px 32px rgba(0,0,0,0.15);
+ }
+
+ .main-header h1 {
+ color: white;
+ font-size: 3rem;
+ font-weight: 700;
+ margin-bottom: 0.5rem;
+ text-shadow: 0 2px 10px rgba(0,0,0,0.3);
+ }
+
+ .main-header p {
+ color: rgba(255, 255, 255, 0.95);
+ font-size: 1.2rem;
+ font-weight: 300;
+ }
+
+ .status-card {
+ background: white;
+ border-radius: 15px;
+ padding: 1rem;
+ margin-bottom: 1.5rem;
+ border: 1px solid #e1e5e9;
+ box-shadow: 0 4px 20px rgba(0,0,0,0.08);
+ }
+
+ .status-card label {
+ color: #2d3748 !important;
+ font-weight: 600 !important;
+ }
+
+ .usage-guide h3 {
+ color: #2d3748 !important;
+ font-weight: 600 !important;
+ margin-bottom: 0.5rem !important;
+ }
+
+ .usage-guide p {
+ color: #4a5568 !important;
+ font-size: 1rem !important;
+ line-height: 1.6 !important;
+ margin: 0.5rem 0 !important;
+ }
+
+ .usage-guide strong {
+ color: #1a202c !important;
+ font-weight: 700 !important;
+ }
+
+ .usage-guide em {
+ color: #1a202c !important;
+ font-weight: 700 !important;
+ font-style: normal !important;
+ }
+
+ .main-interface {
+ margin-bottom: 2rem;
+ }
+
+ .input-section {
+ background: white;
+ border-radius: 20px;
+ padding: 2rem;
+ margin-right: 1rem;
+ box-shadow: 0 8px 32px rgba(0,0,0,0.1);
+ border: 1px solid #e1e5e9;
+ }
+
+ .input-section h3 {
+ color: #2d3748 !important;
+ font-weight: 600 !important;
+ margin-bottom: 1rem !important;
+ }
+
+ .input-section label {
+ color: #4a5568 !important;
+ font-weight: 500 !important;
+ }
+
+ .output-section {
+ background: white;
+ border-radius: 20px;
+ padding: 2rem;
+ margin-left: 1rem;
+ box-shadow: 0 8px 32px rgba(0,0,0,0.1);
+ border: 1px solid #e1e5e9;
+ }
+
+ .output-section h3 {
+ color: #2d3748 !important;
+ font-weight: 600 !important;
+ margin-bottom: 1rem !important;
+ }
+
+ .output-section label {
+ color: #4a5568 !important;
+ font-weight: 500 !important;
+ }
+
+ .examples-section h3 {
+ color: #2d3748 !important;
+ font-weight: 600 !important;
+ margin-bottom: 1.5rem !important;
+ }
+
+ .generate-btn {
+ background: linear-gradient(45deg, #667eea, #764ba2) !important;
+ border: none !important;
+ color: white !important;
+ font-weight: 600 !important;
+ font-size: 1.1rem !important;
+ padding: 12px 30px !important;
+ border-radius: 25px !important;
+ box-shadow: 0 4px 15px rgba(102, 126, 234, 0.4) !important;
+ transition: all 0.3s ease !important;
+ }
+
+ .generate-btn:hover {
+ transform: translateY(-2px) !important;
+ box-shadow: 0 8px 25px rgba(102, 126, 234, 0.6) !important;
+ }
+
+
+
+ .examples-section {
+ background: white;
+ border-radius: 20px;
+ padding: 2rem;
+ margin-top: 2rem;
+ box-shadow: 0 8px 32px rgba(0,0,0,0.1);
+ border: 1px solid #e1e5e9;
+ }
+
+ .examples-section p {
+ color: #4a5568 !important;
+ margin-bottom: 1rem !important;
+ }
+
+ .example-row {
+ background: #f8fafc;
+ border: 1px solid #e2e8f0;
+ border-radius: 15px;
+ padding: 1.5rem;
+ margin: 1rem 0;
+ transition: all 0.3s ease;
+ align-items: center;
+ }
+
+ .example-row:hover {
+ border-color: #667eea;
+ transform: translateY(-2px);
+ box-shadow: 0 4px 20px rgba(102, 126, 234, 0.15);
+ }
+
+ .example-row .markdown {
+ color: #2d3748 !important;
+ }
+
+ .example-row .markdown p {
+ color: #2d3748 !important;
+ margin: 0.5rem 0 !important;
+ line-height: 1.5 !important;
+ }
+
+ .example-row .markdown strong {
+ color: #1a202c !important;
+ font-weight: 600 !important;
+ }
+
+ /* Example grid layout styles */
+ .example-grid-row {
+ margin: 1rem 0;
+ gap: 1rem;
+ }
+
+ .example-item {
+ background: #f8fafc;
+ border: 1px solid #e2e8f0;
+ border-radius: 15px;
+ padding: 1rem;
+ transition: all 0.3s ease;
+ margin: 0.25rem;
+ max-width: 250px;
+ margin-left: auto;
+ margin-right: auto;
+ }
+
+ .example-item:hover {
+ border-color: #667eea;
+ transform: translateY(-2px);
+ box-shadow: 0 4px 20px rgba(102, 126, 234, 0.15);
+ }
+
+ .example-caption {
+ margin: 0.5rem 0 !important;
+ min-height: 2.8rem !important;
+ display: flex !important;
+ align-items: flex-start !important;
+ }
+
+ .example-caption p {
+ color: #2d3748 !important;
+ font-size: 0.9rem !important;
+ line-height: 1.4 !important;
+ margin: 0.5rem 0 !important;
+ }
+
+ /* Multi-video gallery styles */
+ .additional-samples {
+ margin-top: 1rem;
+ gap: 0.5rem;
+ }
+
+ .additional-samples .gradio-video {
+ border-radius: 10px;
+ overflow: hidden;
+ }
+
+ /* Video gallery responsive layout */
+ .video-gallery {
+ display: grid;
+ gap: 1rem;
+ margin-top: 1rem;
+ }
+
+ .video-gallery.single {
+ grid-template-columns: 1fr;
+ }
+
+ .video-gallery.dual {
+ grid-template-columns: 1fr 1fr;
+ }
+
+ .video-gallery.multi {
+ grid-template-columns: repeat(2, 1fr);
+ grid-template-rows: auto auto auto;
+ }
+
+ .footer-text {
+ color: #718096 !important;
+ text-align: center;
+ padding: 2rem;
+ font-size: 0.9rem;
+ }
+
+ /* Video component styling for consistent size */
+ .input-section video,
+ .output-section video,
+ .example-row video {
+ width: 100% !important;
+ height: 300px !important;
+ object-fit: contain !important;
+ border-radius: 10px !important;
+ background-color: #000 !important;
+ }
+
+ .example-row video {
+ height: 150px !important;
+ }
+
+ /* Fix for additional samples video display */
+ .additional-samples video {
+ height: 150px !important;
+ object-fit: contain !important;
+ border-radius: 10px !important;
+ background-color: #000 !important;
+ }
+
+ .additional-samples .gradio-video {
+ border-radius: 10px !important;
+ overflow: hidden !important;
+ background-color: #000 !important;
+ }
+
+ .additional-samples .gradio-video > div {
+ background-color: #000 !important;
+ border-radius: 10px !important;
+ }
+
+ /* Video container styling */
+ .input-section .video-container,
+ .output-section .video-container,
+ .example-row .video-container {
+ background-color: #000 !important;
+ border-radius: 10px !important;
+ display: flex !important;
+ align-items: center !important;
+ justify-content: center !important;
+ overflow: hidden !important;
+ }
+
+ /* Ensure proper alignment */
+ .example-row {
+ display: flex !important;
+ align-items: stretch !important;
+ }
+
+ .example-row > div {
+ display: flex !important;
+ flex-direction: column !important;
+ justify-content: center !important;
+ }
+
+ /* Video wrapper for better control */
+ .video-wrapper {
+ position: relative !important;
+ width: 100% !important;
+ background: #000 !important;
+ border-radius: 10px !important;
+ overflow: hidden !important;
+ display: flex !important;
+ align-items: center !important;
+ justify-content: center !important;
+ }
+ """
+
+ with gr.Blocks(css=css, title="HunyuanVideo-Foley") as app:
+
+ # Main header
+ with gr.Column(elem_classes=["main-header"]):
+ gr.HTML("""
+ 🎵 HunyuanVideo-Foley
+ Text-Video-to-Audio Synthesis: Generate realistic audio from video and text descriptions
+ """)
+
+ # Usage Guide
+ with gr.Column(elem_classes=["status-card"]):
+ gr.Markdown("""
+ ### 📋 Quick Start Guide
+ **1.** Upload your video file\t**2.** Add optional text description\t**3.** Adjust sample numbers (1-6)\t**4.** Click Generate Audio
+
+ 💡 For quick start, you can load the prepared examples by clicking the button.
+ """, elem_classes=["usage-guide"])
+
+ # Main inference interface - Input and Results side by side
+ with gr.Row(elem_classes=["main-interface"]):
+ # Input section
+ with gr.Column(scale=1, elem_classes=["input-section"]):
+ gr.Markdown("### 📹 Video Input")
+
+ video_input = gr.Video(
+ label="Upload Video",
+ info="Supported formats: MP4, AVI, MOV, etc.",
+ height=300
+ )
+
+ text_input = gr.Textbox(
+ label="🎯 Audio Description (English)",
+ placeholder="A person walks on frozen ice",
+ lines=3,
+ info="Describe the audio you want to generate (optional)"
+ )
+
+ with gr.Row():
+ guidance_scale = gr.Slider(
+ minimum=1.0,
+ maximum=10.0,
+ value=4.5,
+ step=0.1,
+ label="🎚️ CFG Scale",
+ )
+
+ inference_steps = gr.Slider(
+ minimum=10,
+ maximum=100,
+ value=50,
+ step=5,
+ label="⚡ Steps",
+ )
+
+ sample_nums = gr.Slider(
+ minimum=1,
+ maximum=6,
+ value=1,
+ step=1,
+ label="🎲 Sample Nums",
+ )
+
+ generate_btn = gr.Button(
+ "🎵 Generate Audio",
+ variant="primary",
+ elem_classes=["generate-btn"]
+ )
+
+ # Results section
+ with gr.Column(scale=1, elem_classes=["output-section"]):
+ gr.Markdown("### 🎥 Generated Results")
+
+ # Multi-video gallery for displaying multiple generated samples
+ with gr.Column():
+ # Primary video (Sample 1)
+ video_output_1 = gr.Video(
+ label="Sample 1",
+ height=250,
+ visible=True
+ )
+
+ # Additional videos (Samples 2-6) - initially hidden
+ with gr.Row(elem_classes=["additional-samples"]):
+ with gr.Column(scale=1):
+ video_output_2 = gr.Video(
+ label="Sample 2",
+ height=150,
+ visible=False
+ )
+ video_output_3 = gr.Video(
+ label="Sample 3",
+ height=150,
+ visible=False
+ )
+ with gr.Column(scale=1):
+ video_output_4 = gr.Video(
+ label="Sample 4",
+ height=150,
+ visible=False
+ )
+ video_output_5 = gr.Video(
+ label="Sample 5",
+ height=150,
+ visible=False
+ )
+
+ # Sample 6 - full width
+ video_output_6 = gr.Video(
+ label="Sample 6",
+ height=150,
+ visible=False
+ )
+
+ result_text = gr.Textbox(
+ label="Status",
+ interactive=False,
+ lines=2
+ )
+
+ # Examples section at the bottom
+ with gr.Column(elem_classes=["examples-section"]):
+ gr.Markdown("### 🌟 Examples")
+ gr.Markdown("Click on any example to load it into the interface above")
+
+ # Define your custom examples here - 8 examples total
+ examples_data = [
+ # Example 1
+ {
+ "caption": "A person walks on frozen ice",
+ "video_path": "examples/1_video.mp4",
+ "result_path": "examples/1_result.mp4"
+ },
+ # Example 2
+ {
+ "caption": "With a faint sound as their hands parted, the two embraced, a soft 'mm' escaping between them.",
+ "video_path": "examples/2_video.mp4",
+ "result_path": "examples/2_result.mp4"
+ },
+ # Example 3
+ {
+ "caption": "The sound of the number 3's bouncing footsteps is as light and clear as glass marbles hitting the ground. Each step carries a magical sound.",
+ "video_path": "examples/3_video.mp4",
+ "result_path": "examples/3_result.mp4"
+ },
+ # Example 4
+ {
+ "caption": "gentle gurgling of the stream's current, and music plays in the background which is a beautiful and serene piano solo with a hint of classical charm, evoking a sense of peace and serenity in people's hearts.",
+ "video_path": "examples/4_video.mp4",
+ "result_path": "examples/4_result.mp4"
+ },
+ # Example 5 - Add your new examples here
+ {
+ "caption": "snow crunching under the snowboard's edge.",
+ "video_path": "examples/5_video.mp4",
+ "result_path": "examples/5_result.mp4"
+ },
+ # Example 6
+ {
+ "caption": "The crackling of the fire, the whooshing of the flames, and the occasional crisp popping of charred leaves filled the forest.",
+ "video_path": "examples/6_video.mp4",
+ "result_path": "examples/6_result.mp4"
+ },
+ # Example 7
+ {
+ "caption": "humming of the scooter engine accelerates slowly.",
+ "video_path": "examples/7_video.mp4",
+ "result_path": "examples/7_result.mp4"
+ },
+ # Example 8
+ {
+ "caption": "splash of water and loud thud as person hits the surface.",
+ "video_path": "examples/8_video.mp4",
+ "result_path": "examples/8_result.mp4"
+ }
+ ]
+
+ # Create example grid - 4 examples per row, 2 rows total
+ example_buttons = []
+ for row in range(2): # 2 rows
+ with gr.Row(elem_classes=["example-grid-row"]):
+ for col in range(4): # 4 columns
+ idx = row * 4 + col
+ if idx < len(examples_data):
+ example = examples_data[idx]
+
+ with gr.Column(scale=1, elem_classes=["example-item"]):
+ # Video thumbnail
+ if os.path.exists(example['video_path']):
+ example_video = gr.Video(
+ value=example['video_path'],
+ label=f"Example {idx+1}",
+ interactive=False,
+ show_label=True,
+ height=180
+ )
+ else:
+ example_video = gr.HTML(f"""
+
+
+
📹 Video not found
+
{example['video_path']}
+
+