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@@ -24,10 +24,15 @@ Research and development for automated ball-strike officiating systems
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  2. Training Data
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  Dataset Source
 
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  Base dataset: ROBO ump Roboflow Universe, accessed 2025
 
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  https://universe.roboflow.com/toasty-workspace/roboump
 
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  Platform: Roboflow Universe (roboflow.com/universe)
 
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  Collection: Broadcast MLB footage (center-field fixed-angle camera)
 
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  Resolution: 640 × 640 px (resized)
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  Class Distribution
@@ -69,22 +74,30 @@ Overall Metrics
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  mAP@50: 0.92 (target > 0.85)
 
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  Overall F1: 0.91 (target >= 0.80)
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  Per-Class Breakdown
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  ball: mAP@50 = 0.72, F1 = 0.76
 
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  batter: mAP@50 = 0.97, F1 = 0.95
 
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  pitcher: mAP@50 = 0.97, F1 = 0.84
 
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  strike_zone: mAP@50 = 0.82, F1 = 0.88
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  Confusion Matrix Summary
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  ![confusion_matrix](https://cdn-uploads.huggingface.co/production/uploads/697294cf06dbc59ddb0601f0/5PMZO_0lhXkPzC452UcQB.png)
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  Ball: 69 correctly predicted, 33 missed as background (~32% miss rate)
 
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  Batter: 145/145 correct
 
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  Pitcher: 145/145 correct
 
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  Strike_zone: 44/47 correct, 3 missed as background
 
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  Background false positives: 9 labeled as ball, 4 as strike_zone
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  Performance Analysis
@@ -94,12 +107,13 @@ The ball class is the most critical failure point. A mAP@50 of 0.72 means roughl
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  5. Limitations and Biases
 
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  Known Failure Cases
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  Ball near white uniforms: Low contrast causes false negatives when the ball overlaps light-colored jerseys
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  Strike zone partially off-frame: Bounding box gets truncated when the batter stands near the frame edge
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  Occlusion: When the catcher, batter, or pitcher obscures the ball at the plate, recall drops significantly
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- Low-light or compressed frames: JPEG artifacts confuse the detector, especially for the small ball class
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  Poor-Performing Class: Ball
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  The ball class is the weakest performer (mAP@50 = 0.72) because the ball is typically only 10-20 pixels across at broadcast resolution and moves at 80-100 mph, causing motion blur in standard 30fps footage. Background crowd balls and logos also created false positives requiring manual cleanup.
 
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  2. Training Data
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  Dataset Source
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+
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  Base dataset: ROBO ump Roboflow Universe, accessed 2025
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  https://universe.roboflow.com/toasty-workspace/roboump
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+
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  Platform: Roboflow Universe (roboflow.com/universe)
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  Collection: Broadcast MLB footage (center-field fixed-angle camera)
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  Resolution: 640 × 640 px (resized)
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  Class Distribution
 
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  mAP@50: 0.92 (target > 0.85)
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+
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  Overall F1: 0.91 (target >= 0.80)
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  Per-Class Breakdown
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  ball: mAP@50 = 0.72, F1 = 0.76
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+
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  batter: mAP@50 = 0.97, F1 = 0.95
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+
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  pitcher: mAP@50 = 0.97, F1 = 0.84
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+
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  strike_zone: mAP@50 = 0.82, F1 = 0.88
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  Confusion Matrix Summary
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  ![confusion_matrix](https://cdn-uploads.huggingface.co/production/uploads/697294cf06dbc59ddb0601f0/5PMZO_0lhXkPzC452UcQB.png)
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  Ball: 69 correctly predicted, 33 missed as background (~32% miss rate)
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  Batter: 145/145 correct
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+
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  Pitcher: 145/145 correct
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+
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  Strike_zone: 44/47 correct, 3 missed as background
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+
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  Background false positives: 9 labeled as ball, 4 as strike_zone
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  Performance Analysis
 
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  5. Limitations and Biases
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+
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  Known Failure Cases
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  Ball near white uniforms: Low contrast causes false negatives when the ball overlaps light-colored jerseys
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  Strike zone partially off-frame: Bounding box gets truncated when the batter stands near the frame edge
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  Occlusion: When the catcher, batter, or pitcher obscures the ball at the plate, recall drops significantly
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+ Low-light or compressed frames: JPEG artifacts confuse the detector, especially for the small ball class: After a pitch is completed the broadcast will visualize where the ball landed, this was a cause of false positives.
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  Poor-Performing Class: Ball
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  The ball class is the weakest performer (mAP@50 = 0.72) because the ball is typically only 10-20 pixels across at broadcast resolution and moves at 80-100 mph, causing motion blur in standard 30fps footage. Background crowd balls and logos also created false positives requiring manual cleanup.