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ultralytics 8.1.21 Add YOLOv8-World-v2 models (#8580)

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Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>
Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>
Co-authored-by: UltralyticsAssistant <web@ultralytics.com>
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Laughing 2024-03-04 05:56:57 +08:00 • committed by GitHub
parent 906b8d31dc
commit 946e18f79c
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12 changed files with 98 additions and 48 deletions
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36
ultralytics/utils/benchmarks.py
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@ -32,7 +32,7 @@ from pathlib import Path
import numpy as np
import torch.cuda
from ultralytics import YOLO
from ultralytics import YOLO, YOLOWorld
from ultralytics.cfg import TASK2DATA, TASK2METRIC
from ultralytics.engine.exporter import export_formats
from ultralytics.utils import ASSETS, LINUX, LOGGER, MACOS, TQDM, WEIGHTS_DIR
@ -84,14 +84,20 @@ def benchmark(
emoji, filename = "❌", None # export defaults
try:
# Checks
if i == 9:
if i == 9: # Edge TPU
assert LINUX, "Edge TPU export only supported on Linux"
elif i == 7:
elif i == 7: # TF GraphDef
assert model.task != "obb", "TensorFlow GraphDef not supported for OBB task"
elif i in {5, 10}: # CoreML and TF.js
assert MACOS or LINUX, "export only supported on macOS and Linux"
if i in {3, 5}: # CoreML and OpenVINO
assert not IS_PYTHON_3_12, "CoreML and OpenVINO not supported on Python 3.12"
if i in {6, 7, 8, 9, 10}: # All TF formats
assert not isinstance(model, YOLOWorld), "YOLOWorldv2 TensorFlow exports not supported by onnx2tf yet"
if i in {11}: # Paddle
assert not isinstance(model, YOLOWorld), "YOLOWorldv2 Paddle exports not supported yet"
if i in {12}: # NCNN
assert not isinstance(model, YOLOWorld), "YOLOWorldv2 NCNN exports not supported yet"
if "cpu" in device.type:
assert cpu, "inference not supported on CPU"
if "cuda" in device.type:
@ -261,7 +267,8 @@ class ProfileModels:
"""
return 0.0, 0.0, 0.0, 0.0 # return (num_layers, num_params, num_gradients, num_flops)
def iterative_sigma_clipping(self, data, sigma=2, max_iters=3):
@staticmethod
def iterative_sigma_clipping(data, sigma=2, max_iters=3):
"""Applies an iterative sigma clipping algorithm to the given data times number of iterations."""
data = np.array(data)
for _ in range(max_iters):
@ -359,9 +366,13 @@ class ProfileModels:
def generate_table_row(self, model_name, t_onnx, t_engine, model_info):
"""Generates a formatted string for a table row that includes model performance and metric details."""
layers, params, gradients, flops = model_info
return f"| {model_name:18s} | {self.imgsz} | - | {t_onnx[0]:.2f} ± {t_onnx[1]:.2f} ms | {t_engine[0]:.2f} ± {t_engine[1]:.2f} ms | {params / 1e6:.1f} | {flops:.1f} |"
return (
f"| {model_name:18s} | {self.imgsz} | - | {t_onnx[0]:.2f} ± {t_onnx[1]:.2f} ms | {t_engine[0]:.2f} ± "
f"{t_engine[1]:.2f} ms | {params / 1e6:.1f} | {flops:.1f} |"
)
def generate_results_dict(self, model_name, t_onnx, t_engine, model_info):
@staticmethod
def generate_results_dict(model_name, t_onnx, t_engine, model_info):
"""Generates a dictionary of model details including name, parameters, GFLOPS and speed metrics."""
layers, params, gradients, flops = model_info
return {
@ -372,11 +383,18 @@ class ProfileModels:
"model/speed_TensorRT(ms)": round(t_engine[0], 3),
}
def print_table(self, table_rows):
@staticmethod
def print_table(table_rows):
"""Formats and prints a comparison table for different models with given statistics and performance data."""
gpu = torch.cuda.get_device_name(0) if torch.cuda.is_available() else "GPU"
header = f"| Model | size<br><sup>(pixels) | mAP<sup>val<br>50-95 | Speed<br><sup>CPU ONNX<br>(ms) | Speed<br><sup>{gpu} TensorRT<br>(ms) | params<br><sup>(M) | FLOPs<br><sup>(B) |"
separator = "|-------------|---------------------|--------------------|------------------------------|-----------------------------------|------------------|-----------------|"
header = (
f"| Model | size<br><sup>(pixels) | mAP<sup>val<br>50-95 | Speed<br><sup>CPU ONNX<br>(ms) | "
f"Speed<br><sup>{gpu} TensorRT<br>(ms) | params<br><sup>(M) | FLOPs<br><sup>(B) |"
)
separator = (
"|-------------|---------------------|--------------------|------------------------------|"
"-----------------------------------|------------------|-----------------|"
)
print(f"\n\n{header}")
print(separator)