feat(detector): add CUDA support for ONNX face detection
This commit is contained in:
42
Cargo.lock
generated
42
Cargo.lock
generated
@@ -1271,13 +1271,14 @@ dependencies = [
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"image 0.25.6",
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"imageproc",
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"itertools 0.14.0",
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"linfa",
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"mnn",
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"mnn-bridge",
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"mnn-sync",
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"nalgebra 0.34.0",
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"ndarray",
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"ndarray-image",
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"ndarray-math 0.1.0 (git+https://git.darksailor.dev/servius/ndarray-math)",
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"ndarray-math",
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"ndarray-resize",
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"ndarray-safetensors",
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"ordered-float",
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@@ -2916,6 +2917,19 @@ dependencies = [
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"vcpkg",
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]
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[[package]]
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name = "linfa"
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version = "0.7.1"
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source = "git+https://github.com/relf/linfa?branch=upgrade-ndarray-0.16#c1fbee7c54e806de3f5fb2c5240ce163d000f1ba"
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dependencies = [
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"approx",
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"ndarray",
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"num-traits",
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"rand 0.8.5",
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"sprs",
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"thiserror 2.0.15",
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]
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[[package]]
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name = "linux-raw-sys"
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version = "0.4.15"
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@@ -3223,6 +3237,7 @@ version = "0.16.1"
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source = "registry+https://github.com/rust-lang/crates.io-index"
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checksum = "882ed72dce9365842bf196bdeedf5055305f11fc8c03dee7bb0194a6cad34841"
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dependencies = [
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"approx",
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"matrixmultiply",
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"num-complex",
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"num-integer",
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@@ -3244,16 +3259,7 @@ dependencies = [
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[[package]]
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name = "ndarray-math"
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version = "0.1.0"
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dependencies = [
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"ndarray",
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"num",
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"thiserror 2.0.15",
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]
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[[package]]
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name = "ndarray-math"
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version = "0.1.0"
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source = "git+https://git.darksailor.dev/servius/ndarray-math#f047966f20835267f20e5839272b9ab36c445796"
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source = "git+https://git.darksailor.dev/servius/ndarray-math#df17c36193df60e070e4e120c9feebe68ff3f517"
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dependencies = [
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"ndarray",
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"num",
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@@ -5120,6 +5126,18 @@ dependencies = [
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"bitflags 2.9.2",
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]
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[[package]]
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name = "sprs"
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version = "0.11.3"
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source = "registry+https://github.com/rust-lang/crates.io-index"
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checksum = "8bff8419009a08f6cb7519a602c5590241fbff1446bcc823c07af15386eb801b"
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dependencies = [
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"ndarray",
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"num-complex",
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"num-traits",
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"smallvec 1.15.1",
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]
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[[package]]
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name = "sqlite-loadable"
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version = "0.0.5"
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@@ -5149,7 +5167,7 @@ name = "sqlite3-safetensor-cosine"
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version = "0.1.0"
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dependencies = [
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"ndarray",
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"ndarray-math 0.1.0",
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"ndarray-math",
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"ndarray-safetensors",
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"sqlite-loadable",
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]
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45
Cargo.toml
45
Cargo.toml
@@ -1,43 +1,42 @@
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[workspace]
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members = [
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"ndarray-image",
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"ndarray-resize",
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".",
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"bounding-box",
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"ndarray-safetensors",
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"sqlite3-safetensor-cosine",
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"ndcv-bridge",
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"bbox",
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"ndarray-image",
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"ndarray-resize",
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".",
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"bounding-box",
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"ndarray-safetensors",
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"sqlite3-safetensor-cosine",
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"ndcv-bridge",
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"bbox",
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]
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[workspace.package]
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version = "0.1.0"
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edition = "2024"
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[patch.crates-io]
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linfa = { git = "https://github.com/relf/linfa", branch = "upgrade-ndarray-0.16" }
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[workspace.dependencies]
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bbox = { path = "bbox" }
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divan = { version = "0.1.21" }
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ndarray-npy = "0.9.1"
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serde = { version = "1.0", features = ["derive"] }
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ndarray-image = { path = "ndarray-image" }
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ndarray-resize = { path = "ndarray-resize" }
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mnn = { git = "https://github.com/uttarayan21/mnn-rs", version = "0.2.0", features = [
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# "metal",
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# "coreml",
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"tracing",
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# "metal",
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# "coreml",
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"tracing",
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], branch = "restructure-tensor-type" }
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mnn-bridge = { git = "https://github.com/uttarayan21/mnn-rs", version = "0.1.0", features = [
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"ndarray",
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"ndarray",
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], branch = "restructure-tensor-type" }
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mnn-sync = { git = "https://github.com/uttarayan21/mnn-rs", version = "0.1.0", features = [
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"tracing",
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"tracing",
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], branch = "restructure-tensor-type" }
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nalgebra = { version = "0.34.0", default-features = false, features = ["std"] }
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opencv = { version = "0.95.1" }
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bounding-box = { path = "bounding-box" }
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ndarray-safetensors = { path = "ndarray-safetensors" }
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wide = "0.7.33"
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rayon = "1.11.0"
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bytemuck = "1.23.2"
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error-stack = "0.5.0"
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thiserror = "2.0"
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@@ -76,9 +75,10 @@ color = "0.3.1"
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itertools = "0.14.0"
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ordered-float = "5.0.0"
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ort = { version = "2.0.0-rc.10", default-features = false, features = [
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"std",
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"tracing",
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"ndarray",
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"std",
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"tracing",
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"ndarray",
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"cuda",
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] }
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ndarray-math = { git = "https://git.darksailor.dev/servius/ndarray-math", version = "0.1.0" }
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ndarray-safetensors = { version = "0.1.0", path = "ndarray-safetensors" }
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@@ -89,12 +89,13 @@ iced = { version = "0.13", features = ["tokio", "image"] }
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rfd = "0.15"
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futures = "0.3"
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imageproc = "0.25"
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linfa = "0.7.1"
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[profile.release]
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debug = true
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[features]
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ort-cuda = ["ort/cuda"]
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ort-cuda = []
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ort-coreml = ["ort/coreml"]
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ort-tensorrt = ["ort/tensorrt"]
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ort-tvm = ["ort/tvm"]
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@@ -103,7 +104,7 @@ ort-directml = ["ort/directml"]
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mnn-metal = ["mnn/metal"]
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mnn-coreml = ["mnn/coreml"]
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default = ["mnn-metal", "mnn-coreml"]
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default = ["ort-cuda"]
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[[test]]
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name = "test_bbox_replacement"
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@@ -5,34 +5,34 @@ workspace = false
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[tasks.convert_facenet]
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command = "MNNConvert"
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args = [
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"-f",
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"ONNX",
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"--modelFile",
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"models/facenet.onnx",
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"--MNNModel",
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"models/facenet.mnn",
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"--fp16",
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"--bizCode",
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"MNN",
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"-f",
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"ONNX",
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"--modelFile",
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"models/facenet.onnx",
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"--MNNModel",
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"models/facenet.mnn",
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"--fp16",
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"--bizCode",
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"MNN",
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]
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workspace = false
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[tasks.convert_retinaface]
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command = "MNNConvert"
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args = [
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"-f",
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"ONNX",
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"--modelFile",
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"models/retinaface.onnx",
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"--MNNModel",
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"models/retinaface.mnn",
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"--fp16",
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"--bizCode",
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"MNN",
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"-f",
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"ONNX",
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"--modelFile",
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"models/retinaface.onnx",
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"--MNNModel",
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"models/retinaface.mnn",
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"--fp16",
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"--bizCode",
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"MNN",
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]
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workspace = false
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[tasks.gui]
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command = "cargo"
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args = ["run", "--bin", "gui"]
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args = ["run", "--release", "--bin", "gui"]
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workspace = false
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19
flake.nix
19
flake.nix
@@ -43,6 +43,8 @@
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system: let
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pkgs = import nixpkgs {
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inherit system;
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config.allowUnfree = true;
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config.cudaSupport = pkgs.stdenv.isLinux;
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overlays = [
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rust-overlay.overlays.default
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(final: prev: {
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@@ -75,7 +77,7 @@
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craneLib = (crane.mkLib pkgs).overrideToolchain stableToolchain;
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craneLibLLvmTools = (crane.mkLib pkgs).overrideToolchain stableToolchainWithLLvmTools;
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ort_static = pkgs.onnxruntime.overrideAttrs (old: {
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ort_static = (pkgs.onnxruntime.overide {cudaSupport = true;}).overrideAttrs (old: {
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cmakeFlags =
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old.cmakeFlags
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++ [
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@@ -198,8 +200,9 @@
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devShells = {
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default = pkgs.mkShell.override {stdenv = pkgs.clangStdenv;} (
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commonArgs
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// {
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// rec {
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LLDB_DEBUGSERVER_PATH = "/Applications/Xcode.app/Contents/SharedFrameworks/LLDB.framework/Versions/A/Resources/debugserver";
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LD_LIBRARY_PATH = "$LD_LIBRARY_PATH:${builtins.toString (pkgs.lib.makeLibraryPath packages)}";
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packages = with pkgs;
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[
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stableToolchainWithRustAnalyzer
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@@ -215,6 +218,18 @@
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]
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++ (lib.optionals pkgs.stdenv.isDarwin [
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apple-sdk_13
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])
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++ (lib.optionals pkgs.stdenv.isLinux [
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xorg.libX11
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xorg.libXcursor
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xorg.libXrandr
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xorg.libXi
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xorg.libxcb
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libxkbcommon
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vulkan-loader
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wayland
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zenity
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cudatoolkit
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]);
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}
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);
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@@ -8,7 +8,7 @@ crate-type = ["cdylib", "staticlib"]
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[dependencies]
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ndarray = "0.16.1"
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# ndarray-math = { git = "https://git.darksailor.dev/servius/ndarray-math", version = "0.1.0" }
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ndarray-math = { path = "/Users/fs0c131y/Projects/ndarray-math", version = "0.1.0" }
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ndarray-math = { git = "https://git.darksailor.dev/servius/ndarray-math", version = "0.1.0" }
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# ndarray-math = { path = "/Users/fs0c131y/Projects/ndarray-math", version = "0.1.0" }
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ndarray-safetensors = { version = "0.1.0", path = "../ndarray-safetensors" }
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sqlite-loadable = "0.0.5"
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@@ -22,10 +22,12 @@ const FACENET_MODEL_ONNX: &[u8] =
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include_bytes!(concat!(env!("CARGO_MANIFEST_DIR"), "/models/facenet.onnx"));
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pub fn main() -> Result<()> {
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tracing_subscriber::fmt()
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.with_env_filter("info")
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.with_thread_ids(true)
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.with_thread_names(true)
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.with_target(false)
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.with_env_filter("info,ort=warn")
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// .with_thread_ids(true)
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// .with_thread_names(true)
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.with_file(true)
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.with_line_number(true)
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.with_target(true)
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.init();
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let args = <cli::Cli as clap::Parser>::parse();
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match args.cmd {
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@@ -2,9 +2,9 @@ use detector::errors::*;
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fn main() -> Result<()> {
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// Initialize logging
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tracing_subscriber::fmt()
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.with_env_filter("info")
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// .with_thread_ids(true)
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// .with_file(true)
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.with_env_filter("warn,ort=warn")
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.with_file(true)
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.with_line_number(true)
|
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// .with_thread_names(true)
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.with_target(true)
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.init();
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|
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@@ -1,5 +1,5 @@
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use iced::{
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Alignment, Element, Length, Task, Theme,
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Alignment, Element, Length, Settings, Task, Theme,
|
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widget::{
|
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Space, button, column, container, image, pick_list, progress_bar, row, scrollable, slider,
|
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text,
|
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@@ -57,9 +57,13 @@ pub enum Tab {
|
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#[derive(Debug, Clone, PartialEq)]
|
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pub enum ExecutorType {
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MnnCpu,
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#[cfg(feature = "mnn-metal")]
|
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MnnMetal,
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#[cfg(feature = "mnn-coreml")]
|
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MnnCoreML,
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OnnxCpu,
|
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#[cfg(feature = "ort-cuda")]
|
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OrtCuda,
|
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}
|
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|
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#[derive(Debug, Clone)]
|
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@@ -129,7 +133,10 @@ impl Default for FaceDetectorApp {
|
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output_path: None,
|
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threshold: 0.8,
|
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nms_threshold: 0.3,
|
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#[cfg(not(any(feature = "mnn-metal", feature = "ort-cuda")))]
|
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executor_type: ExecutorType::MnnCpu,
|
||||
#[cfg(feature = "ort-cuda")]
|
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executor_type: ExecutorType::OrtCuda,
|
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is_processing: false,
|
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progress: 0.0,
|
||||
status_message: "Ready".to_string(),
|
||||
@@ -939,12 +946,17 @@ impl FaceDetectorApp {
|
||||
}
|
||||
|
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fn settings_view(&self) -> Element<'_, Message> {
|
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let executor_options = vec![
|
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ExecutorType::MnnCpu,
|
||||
ExecutorType::MnnMetal,
|
||||
ExecutorType::MnnCoreML,
|
||||
ExecutorType::OnnxCpu,
|
||||
];
|
||||
#[allow(unused_mut)]
|
||||
let mut executor_options = vec![ExecutorType::MnnCpu, ExecutorType::OnnxCpu];
|
||||
|
||||
#[cfg(feature = "mnn-metal")]
|
||||
executor_options.push(ExecutorType::MnnMetal);
|
||||
|
||||
#[cfg(feature = "mnn-coreml")]
|
||||
executor_options.push(ExecutorType::MnnCoreML);
|
||||
|
||||
#[cfg(feature = "ort-cuda")]
|
||||
executor_options.push(ExecutorType::OrtCuda);
|
||||
|
||||
container(
|
||||
column![
|
||||
@@ -990,9 +1002,13 @@ impl std::fmt::Display for ExecutorType {
|
||||
fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
|
||||
match self {
|
||||
ExecutorType::MnnCpu => write!(f, "MNN (CPU)"),
|
||||
#[cfg(feature = "mnn-metal")]
|
||||
ExecutorType::MnnMetal => write!(f, "MNN (Metal)"),
|
||||
#[cfg(feature = "mnn-coreml")]
|
||||
ExecutorType::MnnCoreML => write!(f, "MNN (CoreML)"),
|
||||
ExecutorType::OnnxCpu => write!(f, "ONNX (CPU)"),
|
||||
#[cfg(feature = "ort-cuda")]
|
||||
ExecutorType::OrtCuda => write!(f, "ONNX (CUDA)"),
|
||||
}
|
||||
}
|
||||
}
|
||||
@@ -1023,10 +1039,15 @@ fn convert_face_rois_to_handles(face_rois: Vec<ndarray::Array3<u8>>) -> Vec<imag
|
||||
}
|
||||
|
||||
pub fn run() -> iced::Result {
|
||||
let settings = Settings {
|
||||
antialiasing: true,
|
||||
..Default::default()
|
||||
};
|
||||
iced::application(
|
||||
"Face Detector",
|
||||
FaceDetectorApp::update,
|
||||
FaceDetectorApp::view,
|
||||
)
|
||||
.settings(settings)
|
||||
.run_with(FaceDetectorApp::new)
|
||||
}
|
||||
|
||||
@@ -114,17 +114,34 @@ impl FaceDetectionBridge {
|
||||
|
||||
// Create detector and detect faces
|
||||
let faces = match executor_type {
|
||||
ExecutorType::MnnCpu | ExecutorType::MnnMetal | ExecutorType::MnnCoreML => {
|
||||
let forward_type = match executor_type {
|
||||
ExecutorType::MnnCpu => mnn::ForwardType::CPU,
|
||||
ExecutorType::MnnMetal => mnn::ForwardType::Metal,
|
||||
ExecutorType::MnnCoreML => mnn::ForwardType::CoreML,
|
||||
_ => unreachable!(),
|
||||
};
|
||||
|
||||
ExecutorType::MnnCpu => {
|
||||
let mut detector = retinaface::mnn::FaceDetection::builder(RETINAFACE_MODEL_MNN)
|
||||
.map_err(|e| format!("Failed to create MNN detector: {}", e))?
|
||||
.with_forward_type(forward_type)
|
||||
.with_forward_type(mnn::ForwardType::CPU)
|
||||
.build()
|
||||
.map_err(|e| format!("Failed to build MNN detector: {}", e))?;
|
||||
|
||||
detector
|
||||
.detect_faces(image_array.view(), &config)
|
||||
.map_err(|e| format!("Detection failed: {}", e))?
|
||||
}
|
||||
#[cfg(feature = "mnn-metal")]
|
||||
ExecutorType::MnnMetal => {
|
||||
let mut detector = retinaface::mnn::FaceDetection::builder(RETINAFACE_MODEL_MNN)
|
||||
.map_err(|e| format!("Failed to create MNN detector: {}", e))?
|
||||
.with_forward_type(mnn::ForwardType::Metal)
|
||||
.build()
|
||||
.map_err(|e| format!("Failed to build MNN detector: {}", e))?;
|
||||
|
||||
detector
|
||||
.detect_faces(image_array.view(), &config)
|
||||
.map_err(|e| format!("Detection failed: {}", e))?
|
||||
}
|
||||
#[cfg(feature = "mnn-coreml")]
|
||||
ExecutorType::MnnCoreML => {
|
||||
let mut detector = retinaface::mnn::FaceDetection::builder(RETINAFACE_MODEL_MNN)
|
||||
.map_err(|e| format!("Failed to create MNN detector: {}", e))?
|
||||
.with_forward_type(mnn::ForwardType::CoreML)
|
||||
.build()
|
||||
.map_err(|e| format!("Failed to build MNN detector: {}", e))?;
|
||||
|
||||
@@ -142,6 +159,21 @@ impl FaceDetectionBridge {
|
||||
.detect_faces(image_array.view(), &config)
|
||||
.map_err(|e| format!("Detection failed: {}", e))?
|
||||
}
|
||||
#[cfg(feature = "ort-cuda")]
|
||||
ExecutorType::OrtCuda => {
|
||||
use crate::ort_ep::ExecutionProvider;
|
||||
|
||||
let ep = ExecutionProvider::CUDA;
|
||||
let mut detector = retinaface::ort::FaceDetection::builder(RETINAFACE_MODEL_ONNX)
|
||||
.map_err(|e| format!("Failed to create ONNX CUDA detector: {}", e))?
|
||||
.with_execution_providers([ep])
|
||||
.build()
|
||||
.map_err(|e| format!("Failed to build ONNX CUDA detector: {}", e))?;
|
||||
|
||||
detector
|
||||
.detect_faces(image_array.view(), &config)
|
||||
.map_err(|e| format!("CUDA detection failed: {}", e))?
|
||||
}
|
||||
};
|
||||
|
||||
let faces_count = faces.bbox.len();
|
||||
@@ -195,24 +227,17 @@ impl FaceDetectionBridge {
|
||||
// Create detector and embedder, detect faces and generate embeddings
|
||||
let (image1_faces, image2_faces, image1_rois, image2_rois, best_similarity) =
|
||||
match executor_type {
|
||||
ExecutorType::MnnCpu | ExecutorType::MnnMetal | ExecutorType::MnnCoreML => {
|
||||
let forward_type = match executor_type {
|
||||
ExecutorType::MnnCpu => mnn::ForwardType::CPU,
|
||||
ExecutorType::MnnMetal => mnn::ForwardType::Metal,
|
||||
ExecutorType::MnnCoreML => mnn::ForwardType::CoreML,
|
||||
_ => unreachable!(),
|
||||
};
|
||||
|
||||
ExecutorType::MnnCpu => {
|
||||
let mut detector =
|
||||
retinaface::mnn::FaceDetection::builder(RETINAFACE_MODEL_MNN)
|
||||
.map_err(|e| format!("Failed to create MNN detector: {}", e))?
|
||||
.with_forward_type(forward_type.clone())
|
||||
.with_forward_type(mnn::ForwardType::CPU)
|
||||
.build()
|
||||
.map_err(|e| format!("Failed to build MNN detector: {}", e))?;
|
||||
|
||||
let mut embedder = facenet::mnn::EmbeddingGenerator::builder(FACENET_MODEL_MNN)
|
||||
.map_err(|e| format!("Failed to create MNN embedder: {}", e))?
|
||||
.with_forward_type(forward_type)
|
||||
.with_forward_type(mnn::ForwardType::CPU)
|
||||
.build()
|
||||
.map_err(|e| format!("Failed to build MNN embedder: {}", e))?;
|
||||
|
||||
@@ -247,7 +272,148 @@ impl FaceDetectionBridge {
|
||||
best_similarity,
|
||||
)
|
||||
}
|
||||
ExecutorType::OnnxCpu => unimplemented!(),
|
||||
#[cfg(feature = "mnn-metal")]
|
||||
ExecutorType::MnnMetal => {
|
||||
let mut detector =
|
||||
retinaface::mnn::FaceDetection::builder(RETINAFACE_MODEL_MNN)
|
||||
.map_err(|e| format!("Failed to create MNN detector: {}", e))?
|
||||
.with_forward_type(mnn::ForwardType::Metal)
|
||||
.build()
|
||||
.map_err(|e| format!("Failed to build MNN detector: {}", e))?;
|
||||
|
||||
let mut embedder = facenet::mnn::EmbeddingGenerator::builder(FACENET_MODEL_MNN)
|
||||
.map_err(|e| format!("Failed to create MNN embedder: {}", e))?
|
||||
.with_forward_type(mnn::ForwardType::Metal)
|
||||
.build()
|
||||
.map_err(|e| format!("Failed to build MNN embedder: {}", e))?;
|
||||
|
||||
let img_1 = run_detection(
|
||||
image1_path,
|
||||
&mut detector,
|
||||
&mut embedder,
|
||||
threshold,
|
||||
nms_threshold,
|
||||
2,
|
||||
)?;
|
||||
let img_2 = run_detection(
|
||||
image2_path,
|
||||
&mut detector,
|
||||
&mut embedder,
|
||||
threshold,
|
||||
nms_threshold,
|
||||
2,
|
||||
)?;
|
||||
|
||||
let image1_rois = img_1.rois;
|
||||
let image2_rois = img_2.rois;
|
||||
let image1_bbox_len = img_1.bbox.len();
|
||||
let image2_bbox_len = img_2.bbox.len();
|
||||
let best_similarity = compare_faces(&img_1.embeddings, &img_2.embeddings)?;
|
||||
|
||||
(
|
||||
image1_bbox_len,
|
||||
image2_bbox_len,
|
||||
image1_rois,
|
||||
image2_rois,
|
||||
best_similarity,
|
||||
)
|
||||
}
|
||||
#[cfg(feature = "mnn-coreml")]
|
||||
ExecutorType::MnnCoreML => {
|
||||
let mut detector =
|
||||
retinaface::mnn::FaceDetection::builder(RETINAFACE_MODEL_MNN)
|
||||
.map_err(|e| format!("Failed to create MNN detector: {}", e))?
|
||||
.with_forward_type(mnn::ForwardType::CoreML)
|
||||
.build()
|
||||
.map_err(|e| format!("Failed to build MNN detector: {}", e))?;
|
||||
|
||||
let mut embedder = facenet::mnn::EmbeddingGenerator::builder(FACENET_MODEL_MNN)
|
||||
.map_err(|e| format!("Failed to create MNN embedder: {}", e))?
|
||||
.with_forward_type(mnn::ForwardType::CoreML)
|
||||
.build()
|
||||
.map_err(|e| format!("Failed to build MNN embedder: {}", e))?;
|
||||
|
||||
let img_1 = run_detection(
|
||||
image1_path,
|
||||
&mut detector,
|
||||
&mut embedder,
|
||||
threshold,
|
||||
nms_threshold,
|
||||
2,
|
||||
)?;
|
||||
let img_2 = run_detection(
|
||||
image2_path,
|
||||
&mut detector,
|
||||
&mut embedder,
|
||||
threshold,
|
||||
nms_threshold,
|
||||
2,
|
||||
)?;
|
||||
|
||||
let image1_rois = img_1.rois;
|
||||
let image2_rois = img_2.rois;
|
||||
let image1_bbox_len = img_1.bbox.len();
|
||||
let image2_bbox_len = img_2.bbox.len();
|
||||
let best_similarity = compare_faces(&img_1.embeddings, &img_2.embeddings)?;
|
||||
|
||||
(
|
||||
image1_bbox_len,
|
||||
image2_bbox_len,
|
||||
image1_rois,
|
||||
image2_rois,
|
||||
best_similarity,
|
||||
)
|
||||
}
|
||||
ExecutorType::OnnxCpu => unimplemented!("ONNX face comparison not yet implemented"),
|
||||
#[cfg(feature = "ort-cuda")]
|
||||
ExecutorType::OrtCuda => {
|
||||
use crate::ort_ep::ExecutionProvider;
|
||||
let ep = ExecutionProvider::CUDA;
|
||||
let mut detector =
|
||||
retinaface::ort::FaceDetection::builder(RETINAFACE_MODEL_ONNX)
|
||||
.map_err(|e| format!("Failed to create MNN detector: {}", e))?
|
||||
.with_execution_providers([ep])
|
||||
.build()
|
||||
.map_err(|e| format!("Failed to build MNN detector: {}", e))?;
|
||||
|
||||
let mut embedder =
|
||||
facenet::ort::EmbeddingGenerator::builder(FACENET_MODEL_ONNX)
|
||||
.map_err(|e| format!("Failed to create MNN embedder: {}", e))?
|
||||
.with_execution_providers([ep])
|
||||
.build()
|
||||
.map_err(|e| format!("Failed to build MNN embedder: {}", e))?;
|
||||
|
||||
let img_1 = run_detection(
|
||||
image1_path,
|
||||
&mut detector,
|
||||
&mut embedder,
|
||||
threshold,
|
||||
nms_threshold,
|
||||
2,
|
||||
)?;
|
||||
let img_2 = run_detection(
|
||||
image2_path,
|
||||
&mut detector,
|
||||
&mut embedder,
|
||||
threshold,
|
||||
nms_threshold,
|
||||
2,
|
||||
)?;
|
||||
|
||||
let image1_rois = img_1.rois;
|
||||
let image2_rois = img_2.rois;
|
||||
let image1_bbox_len = img_1.bbox.len();
|
||||
let image2_bbox_len = img_2.bbox.len();
|
||||
let best_similarity = compare_faces(&img_1.embeddings, &img_2.embeddings)?;
|
||||
|
||||
(
|
||||
image1_bbox_len,
|
||||
image2_bbox_len,
|
||||
image1_rois,
|
||||
image2_rois,
|
||||
best_similarity,
|
||||
)
|
||||
}
|
||||
};
|
||||
|
||||
Ok((
|
||||
|
||||
@@ -13,7 +13,7 @@ use ort::execution_providers::TensorRTExecutionProvider;
|
||||
use ort::execution_providers::{CPUExecutionProvider, ExecutionProviderDispatch};
|
||||
|
||||
/// Supported execution providers for ONNX Runtime
|
||||
#[derive(Debug, Clone)]
|
||||
#[derive(Debug, Copy, Clone)]
|
||||
pub enum ExecutionProvider {
|
||||
/// CPU execution provider (always available)
|
||||
CPU,
|
||||
|
||||
Reference in New Issue
Block a user