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Top Slight Computer Vision Models
The models below have been fine-tuned for various slight 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 slight detection model.
At the bottom of this page, we have guides on how to count slights in images and videos.
by osmando
706 images 1342 classes
animal car drink mushroom rock wine glass 2 bottles on a rock next to fruit in front of orange background. 2 brown paper boxes in front of light brown background 2 cream bottles in front of blue tiles 2 macarons on a rock block in front of light orange background 3 black bottles next to yellow stairs and dry flower with shadow 3 blue bottles on blue plates next to dry nuts 3 bottles in front of light background with shadows 3 bottles in front of light brown background with shadows. 3 bottles in front of light gray background with shadows of a plant. 3 boxes in front of dark background 3 perfume bottles on reflective gray surface 4 paper boxes in front of light yellow background 4 potteries on a marble table 6 white bowls of spices on a wooden surface
by Keith
93 images 7 classes
Day 1 - Freshly Harvested (Ready to Consume) Day 2 - Initial Ripening (Ideal time to consume) Day 2-3: Acceptable Maturity (Consumable) Day 3 - Ripening Progression (Consumable) Day 4 - Advanced Ripening (Consumable) Day 4-5: Advanced Ripening (Not Recommended For Consumption) Day 5 - Slight Rot (Not Recommended to Consume)
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