[package]
name = "wifi-densepose-train"
version = "0.1.0"
edition = "2021"
authors = ["WiFi-DensePose Contributors"]
license = "MIT OR Apache-2.0"
description = "Training pipeline for WiFi-DensePose pose estimation"
keywords = ["wifi", "training", "pose-estimation", "deep-learning"]

[[bin]]
name = "train"
path = "src/bin/train.rs"

[[bin]]
name = "verify-training"
path = "src/bin/verify_training.rs"

[features]
default = ["tch-backend"]
tch-backend = ["tch"]
cuda = ["tch-backend"]

[dependencies]
# Internal crates
wifi-densepose-signal = { path = "../wifi-densepose-signal" }
wifi-densepose-nn = { path = "../wifi-densepose-nn", default-features = false }

# Core
thiserror = "1.0"
anyhow = "1.0"
serde = { version = "1.0", features = ["derive"] }
serde_json = "1.0"

# Tensor / math
ndarray = { version = "0.15", features = ["serde"] }
ndarray-linalg = { version = "0.16", features = ["openblas-static"] }
num-complex = "0.4"
num-traits = "0.2"

# PyTorch bindings (training)
tch = { version = "0.14", optional = true }

# Graph algorithms (min-cut for optimal keypoint assignment)
petgraph = "0.6"

# Data loading
ndarray-npy = "0.8"
memmap2 = "0.9"
walkdir = "2.4"

# Serialization
csv = "1.3"
toml = "0.8"

# Logging / progress
tracing = "0.1"
tracing-subscriber = { version = "0.3", features = ["env-filter"] }
indicatif = "0.17"

# Async
tokio = { version = "1.35", features = ["rt", "rt-multi-thread", "macros", "fs"] }

# Crypto (for proof hash)
sha2 = "0.10"

# CLI
clap = { version = "4.4", features = ["derive"] }

# Time
chrono = { version = "0.4", features = ["serde"] }

[dev-dependencies]
criterion = { version = "0.5", features = ["html_reports"] }
proptest = "1.4"
tempfile = "3.10"
approx = "0.5"

[[bench]]
name = "training_bench"
harness = false