You find the outfit, you screenshot it, you upload it, and Snagfit comes back with nothing. That is annoying, and almost every time it is the photo rather than the clothes.
Snagfit reads each garment in a picture on its own: the jacket, the trousers, the shoes, the bag, each identified separately along with its color, cut and material. That is the useful part, and it is also the part that sets the rules. A garment the AI cannot see clearly is a garment it cannot match.
Get the whole outfit in the frame
A full-body shot gives the AI the most to work with. When a photo is cropped at the waist, the trousers and shoes are simply not there to find, so the results come back short and it looks like a miss.
This matters most with video. Scrubbing to roughly the right moment usually lands you on a frame where an arm, a turn, or a passing object is covering half the outfit. Move a second either way and take the screenshot there instead.
Pause on a still moment
A frame grabbed mid-movement is blurred, and blur removes exactly the detail the AI is reading: the weave, the seam lines, the edge where one garment ends and the next begins. A still moment beats a dramatic one every time.
Let nothing block the clothes
Bags, arms, furniture, other people. Anything in front of a garment reads as part of the shape. If the coat is half behind a counter, expect the coat to be the piece that comes back wrong.
What does not matter
A few things people worry about that make no difference:
- File type. JPG, PNG and WEBP all work, and a plain phone screenshot is already one of those.
- File size. Large photos are resized in your browser before anything is sent, so a big camera-roll photo uploads just as quickly as a small one.
- Where it came from. A screenshot from a video, a post, a friend's message or your own camera works the same way. Snagfit reads the image, not its history.
If it still comes back empty
Try a different frame of the same outfit before you give up on it. A second screenshot, one taken a moment earlier or later, is usually enough. The detection is doing the same work each time, so a clearer picture is the one variable actually worth changing.