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Docs Solutions to Navigation Bar (#13249)

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Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>
Co-authored-by: Muhammad Rizwan Munawar <muhammadrizwanmunawar123@gmail.com>
Co-authored-by: UltralyticsAssistant <web@ultralytics.com>
Co-authored-by: Richard Abrich <richard.abrich@gmail.com>
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Glenn Jocher 2024-05-30 22:07:03 +02:00 • committed by GitHub
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7 changed files with 128 additions and 82 deletions
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32
tests/test_cli.py
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@ -3,6 +3,7 @@
import subprocess
import pytest
from PIL import Image
from tests import CUDA_DEVICE_COUNT, CUDA_IS_AVAILABLE
from ultralytics.cfg import TASK2DATA, TASK2MODEL, TASKS
@ -74,26 +75,27 @@ def test_fastsam(task="segment", model=WEIGHTS_DIR / "FastSAM-s.pt", data="coco8
sam_model = FastSAM(model) # or FastSAM-x.pt
# Run inference on an image
everything_results = sam_model(source, device="cpu", retina_masks=True, imgsz=1024, conf=0.4, iou=0.9)
for s in (source, Image.open(source)):
everything_results = sam_model(s, device="cpu", retina_masks=True, imgsz=320, conf=0.4, iou=0.9)
# Remove small regions
new_masks, _ = Predictor.remove_small_regions(everything_results[0].masks.data, min_area=20)
# Remove small regions
new_masks, _ = Predictor.remove_small_regions(everything_results[0].masks.data, min_area=20)
# Everything prompt
prompt_process = FastSAMPrompt(source, everything_results, device="cpu")
ann = prompt_process.everything_prompt()
# Everything prompt
prompt_process = FastSAMPrompt(s, everything_results, device="cpu")
ann = prompt_process.everything_prompt()
# Bbox default shape [0,0,0,0] -> [x1,y1,x2,y2]
ann = prompt_process.box_prompt(bbox=[200, 200, 300, 300])
# Bbox default shape [0,0,0,0] -> [x1,y1,x2,y2]
ann = prompt_process.box_prompt(bbox=[200, 200, 300, 300])
# Text prompt
ann = prompt_process.text_prompt(text="a photo of a dog")
# Text prompt
ann = prompt_process.text_prompt(text="a photo of a dog")
# Point prompt
# Points default [[0,0]] [[x1,y1],[x2,y2]]
# Point_label default [0] [1,0] 0:background, 1:foreground
ann = prompt_process.point_prompt(points=[[200, 200]], pointlabel=[1])
prompt_process.plot(annotations=ann, output="./")
# Point prompt
# Points default [[0,0]] [[x1,y1],[x2,y2]]
# Point_label default [0] [1,0] 0:background, 1:foreground
ann = prompt_process.point_prompt(points=[[200, 200]], pointlabel=[1])
prompt_process.plot(annotations=ann, output="./")
def test_mobilesam():