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Related Objects of Interest: alive , dead , fixed_count , kill_log , map_player_position , message , moving_count , object , other_player , penalty
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Top Lead Computer Vision Models
The models below have been fine-tuned for various lead detection tasks. You can try out each model in your browser, or test an edge deployment solution (i.e. to an NVIDIA Jetson). You can use the datasets associated with the models below as a starting point for building your own lead detection model.
At the bottom of this page, we have guides on how to count leads in images and videos.
752 images 28 classes 1 model
704 images 5 classes 1 model
Risk point：Several vehicles are parked in non-parking areas. Risk point：The presence of motorcycles and bicycles within the same lanes as cars. Risk-point:There-are-pedestrians-walking-and-crossing-the-road-in-between-cars. Risk-point：Some-vehicles-appear-to-be-driving-in-the-wrong-direction. Risk-point：The-high-density-of-vehicles-can-lead-to-congestion.
4.5k images 7 classes 3 models
DISEASE: Narrow Brown Spot NUTRIENT DEFFICIENT: Nitrogen (N), Potassium (K), Calcium (Ca), DISEASE: Bacterial Leaf Blight NUTRIENT DEFFICIENT: Silicon DISEASE: Hispa NUTRIENT DEFFICENCY: N/A ; Integrated pest management practices: DISEASE: Lead Scald NUTRIENT DEFFICIENT: Nitrogen (N), Potassium (K), Calcium (Ca), Sulfur (S) DISEASE: Leaf Smut NUTRIENT DEFFICIENT: N/A Proper field management practices to minimize the spread of the pathogen. HEALTHY ISEASE: Leaf Blast NUTRIENT DEFFICIENT: Silicon, Nitrogen (N), Potassium (K), Potassium (K), Calcium (Ca)
587 images 46 classes 6 models
200 images 7 classes 1 model
39 images 53 classes 1 model
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50 images 11 classes 1 model
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149 images 21 classes 1 model
549 images 7 classes 1 model
1k images 27 classes 1 model
9.7k images 60 classes 1 model
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