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let to_float img = Nx.div_s (Nx.astype Nx.float32 img) 255.0
let to_uint8 img =
let clipped = Nx.clip ~min:0.0 ~max:1.0 img in
Nx.astype Nx.uint8 (Nx.mul_s clipped 255.0)
let normalize ~mean ~std img =
let shape = Nx.shape img in
let rank = Array.length shape in
let c = shape.(rank - 1) in
if List.length mean <> c || List.length std <> c then
invalid_arg
(Printf.sprintf
"normalize: mean/std length (%d/%d) does not match channels (%d)"
(List.length mean) (List.length std) c);
let ones = Array.make rank 1 in
ones.(rank - 1) <- c;
let mean_t =
Nx.reshape ones (Nx.create Nx.float32 [| c |] (Array.of_list mean))
in
let std_t =
Nx.reshape ones (Nx.create Nx.float32 [| c |] (Array.of_list std))
in
Nx.div (Nx.sub img mean_t) std_t
let threshold t img =
let t_s = Nx.scalar_like img t in
let one = Nx.ones_like img in
let zero = Nx.zeros_like img in
Nx.where (Nx.greater img t_s) one zero
include Color
include Transform
include Filter
include Morphology
include Edge