Update README.md
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README.md
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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
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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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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
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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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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
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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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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
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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: 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.
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