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mimo-1.0 / SPEED_OPTIMIZATION_GUIDE.md
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Fix occlusion mask broadcasting error + speed optimization guide
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A newer version of the Gradio SDK is available: 5.49.1

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Speed Optimization & Broadcasting Fix

🐛 Fixed: Occlusion Mask Broadcasting Error

Problem 

ValueError: operands could not be broadcast together with shapes (775,837,3) (1920,1080,1)

Root Cause

The vid_image array had different dimensions (1920×1080) than res_image (775×837), causing broadcasting failure when applying occlusion masks.

Solution

Added dimension matching by resizing vid_image before blending:

# Resize vid_image to match res_image dimensions
if vid_image.shape[:2] != res_image.shape[:2]:
    vid_image = cv2.resize(vid_image, (res_image.shape[1], res_image.shape[0]), interpolation=cv2.INTER_LINEAR)

Status: ✅ Fixed in app_hf_spaces.py

⚡ Speed Optimization Analysis

Current Performance

  • Generation time: 2-5 minutes per video
  • GPU: ZeroGPU (Nvidia A100 40GB, time-shared)
  • Current settings:
    • Resolution: 512×512
    • Inference steps: 20
    • Max frames: 100
    • Frame rate: 30 fps

Why It's Slow

1. ZeroGPU Time-Sharing ⏱️

  • Not a dedicated GPU - shared across many users
  • Queue time: Can add 30-120 seconds before your job starts
  • Time limits: 120 seconds max per generation
  • Cold starts: Model loading takes 30-60 seconds first time

2. Model Complexity 🧠

  • Large models: ~8GB total (VAE, UNet3D, CLIP, etc.)
  • Diffusion process: 20 denoising steps per frame
  • Context windows: Processes frames in batches with overlap

3. Video Processing 🎬

  • Multiple passes: Pose extraction → Generation → Compositing
  • Background blending: Mask operations on each frame
  • Occlusion handling: Additional processing for templates with occlusion masks

🚀 Speed Optimization Options

Option 1: Current Settings (Balanced) ⭐ RECOMMENDED

Status: Already implemented

Resolution: 512×512
Inference steps: 20
Max frames: 100
Quality: Good
Speed: 2-5 minutes

Pros:

  • ✅ Good quality
  • ✅ Reasonable speed
  • ✅ Works within ZeroGPU limits

Cons:

  • ⚠️ Still takes a few minutes
  • ⚠️ Queue time unpredictable

Option 2: Faster Settings (Speed Priority) ⚡

Reduce frames and steps further

Resolution: 512×512  
Inference steps: 15  # Down from 20
Max frames: 60       # Down from 100
Quality: Acceptable
Speed: 1-3 minutes

Implementation:

# In app_hf_spaces.py line ~967
steps = 15 if HAS_SPACES else 20  # Faster on HF

# Line ~937
MAX_FRAMES = 60 if HAS_SPACES else 150  # Shorter videos

Pros:

  • ✅ 30-40% faster
  • ✅ Still acceptable quality

Cons:

  • ⚠️ Slightly lower quality
  • ⚠️ Shorter videos (2 seconds at 30fps)

Option 3: Ultra-Fast Settings (Demo Mode) 🏃

Minimal settings for quick demos

Resolution: 384×384  # Smaller
Inference steps: 10  # Fewer steps
Max frames: 30       # 1 second video
Quality: Lower
Speed: 30-60 seconds

Pros:

  • ✅ Very fast
  • ✅ Good for testing/demos

Cons:

  • ❌ Noticeably lower quality
  • ❌ Very short videos

Option 4: Upgrade to Dedicated GPU 💰

Upgrade HuggingFace Space tier

Current: Free ZeroGPU (shared, time-limited)

Upgrade options:

  1. Spaces GPU Basic ($0.60/hour)

    • Nvidia T4 (16GB dedicated)
    • No time limits
    • ~50% faster (no queue, dedicated)
    • Cost: ~$14/day continuous, $40-50/month light usage

  2. Spaces GPU Upgrade ($3/hour)

    • Nvidia A10G (24GB dedicated)
    • ~2-3x faster than ZeroGPU
    • Better for heavy usage
    • Cost: ~$72/day continuous, $100-200/month light usage

  3. Spaces GPU Pro ($9/hour)

    • Nvidia A100 (40GB dedicated)
    • ~3-4x faster than ZeroGPU
    • Same hardware as ZeroGPU but dedicated
    • Cost: ~$216/day continuous

Recommendation:

  • Free users: Stick with ZeroGPU (current)
  • Light usage: Upgrade to GPU Basic ($0.60/hr)
  • Production: Consider dedicated hosting

How to upgrade:

  1. Go to: https://huggingface.co/spaces/minhho/mimo-1.0/settings
  2. Click "Change hardware"
  3. Select GPU tier
  4. Confirm billing

🎯 Recommended Approach

For Public Demo (Current) ✅

Keep current settings:

  • Resolution: 512×512
  • Steps: 20
  • Max frames: 100
  • Cost: Free
  • Speed: 2-5 minutes
  • Quality: Good

Add user expectations:

  • Update UI to show "⏱️ Expected time: 2-5 minutes"
  • Add progress updates during generation
  • Show queue position if possible

For Production Use 💼

Option A: Optimize code (FREE)

  • Reduce to 15 steps, 60 frames
  • Speed: 1-3 minutes
  • Cost: Free

Option B: Upgrade hardware ($$$)

  • Keep quality settings
  • Upgrade to GPU Basic ($0.60/hr)
  • Speed: 1-2 minutes
  • Cost: ~$40-50/month light usage

📊 Speed Comparison Table

Configuration Resolution Steps Frames GPU Time Quality Cost
Current 512×512 20 100 ZeroGPU 2-5 min Good Free
Fast 512×512 15 60 ZeroGPU 1-3 min Acceptable Free
Ultra-Fast 384×384 10 30 ZeroGPU 30-60s Lower Free
GPU Basic 512×512 20 100 T4 16GB 1-2 min Good $0.60/hr
GPU Upgrade 512×512 25 150 A10G 24GB 1 min Excellent $3/hr
GPU Pro 768×768 30 150 A100 40GB 30-45s Excellent $9/hr

🔧 Implementation

Apply Fast Settings (Code Changes) 

# In app_hf_spaces.py around line 967
if HAS_SPACES:
    steps = 15  # Reduced from 20 for speed
    MAX_FRAMES = 60  # Reduced from 100 for speed

Update UI (User Expectations) 

# Add to status messages
gr.HTML("""
<p>⏱️ <strong>Expected generation time:</strong> 2-5 minutes</p>
<p>💡 <strong>Tip:</strong> First generation may take longer due to model loading</p>
""")

🎬 Conclusion

Current Status

  • ✅ Broadcasting error fixed - videos will generate successfully
  • ✅ Speed is reasonable for free tier (2-5 minutes)
  • ✅ Quality is good with current settings

Recommendations

For Free Users:

  1. ✅ Keep current settings (20 steps, 100 frames)
  2. ✅ Add time expectations to UI
  3. ✅ Consider reducing to 15 steps/60 frames if speed is critical

For Paid Users:

  1. 💰 Upgrade to GPU Basic ($0.60/hr) for 50% speed boost
  2. 💰 Keep quality settings high
  3. 💰 Cost: ~$40-50/month for light usage

No need to upgrade for demo/testing - current speed is acceptable for free tier!

📝 Files Changed

  • ✅ app_hf_spaces.py - Fixed vid_image broadcasting error
  • ✅ SPEED_OPTIMIZATION_GUIDE.md - This document

Next Steps

  1. Deploy fix: Push code to fix broadcasting error
  2. Test: Generate video with occlusion mask templates
  3. Monitor: Check actual generation times
  4. Decide: Keep free tier or upgrade based on usage

Speed is acceptable for a free demo! 🎉