Ben_Kosytorz
3a67c0979c
- Updated stablediffusion crate path from "../stable-diffusion-burn" to "./crates/stable-diffusion-burn" for proper workspace resolution - Enhanced .gitignore to include generated model files (.mpk, .pt, .bin, .safetensors, .ckpt) and user_data directory - Added Cargo.lock to gitignore with appropriate comment - Reorganized IDE files section in gitignore for better clarity - Added newline at end of file for proper formatting
93 lines
2.3 KiB
Rust
93 lines
2.3 KiB
Rust
use burn_vision::{Nms, NmsOptions};
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mod common;
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use common::*;
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#[test]
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fn should_suppress_non_maximum() {
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let boxes = TestTensor::<2>::from([
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[0, 0, 100, 100],
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[0, 1, 100, 100],
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[0, 101, 200, 200],
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[0, 100, 200, 200],
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[0, 170, 300, 300],
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]);
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let scores = TestTensor::<1>::from([0.1, 0.2, 0.4, 0.3, 0.5]);
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let options = NmsOptions {
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iou_threshold: 0.5,
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score_threshold: 0.0,
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max_output_boxes: 0,
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};
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let output = boxes.nms(scores, options);
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let expected = TestTensorInt::<1>::from([4, 2, 1]);
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output.into_data().assert_eq(&expected.into_data(), true);
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}
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#[test]
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fn should_apply_score_threshold() {
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let boxes = TestTensor::<2>::from([
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[0, 0, 100, 100],
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[0, 1, 100, 100],
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[0, 101, 200, 200],
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[0, 100, 200, 200],
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[0, 170, 300, 300],
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]);
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let scores = TestTensor::<1>::from([0.1, 0.2, 0.4, 0.3, 0.5]);
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let options = NmsOptions {
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iou_threshold: 0.5,
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score_threshold: 0.3,
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max_output_boxes: 0,
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};
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let output = boxes.nms(scores, options);
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let expected = TestTensorInt::<1>::from([4, 2]);
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output.into_data().assert_eq(&expected.into_data(), true);
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}
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#[test]
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fn should_apply_iou_threshold() {
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let boxes = TestTensor::<2>::from([
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[0, 0, 100, 100],
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[0, 1, 100, 100],
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[0, 101, 200, 200],
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[0, 100, 200, 200],
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[0, 170, 300, 300],
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]);
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let scores = TestTensor::<1>::from([0.1, 0.2, 0.4, 0.3, 0.5]);
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let options = NmsOptions {
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iou_threshold: 0.1,
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score_threshold: 0.0,
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max_output_boxes: 0,
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};
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let output = boxes.nms(scores, options);
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let expected = TestTensorInt::<1>::from([4, 1]);
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output.into_data().assert_eq(&expected.into_data(), true);
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}
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#[test]
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fn should_apply_max_output_boxes() {
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let boxes = TestTensor::<2>::from([
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[0, 0, 100, 100],
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[0, 1, 100, 100],
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[0, 101, 200, 200],
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[0, 100, 200, 200],
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[0, 170, 300, 300],
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]);
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let scores = TestTensor::<1>::from([0.1, 0.2, 0.4, 0.3, 0.5]);
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let options = NmsOptions {
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iou_threshold: 0.5,
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score_threshold: 0.0,
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max_output_boxes: 1,
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};
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let output = boxes.nms(scores, options);
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let expected = TestTensorInt::<1>::from([4]);
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output.into_data().assert_eq(&expected.into_data(), true);
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}
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