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Updated SQL Query Plot Code (#8120)

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Co-authored-by: Ayush Chaurasia <ayush.chaurarsia@gmail.com>
Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>
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Ankan Ghosh 2024-02-11 17:28:57 +05:30 committed by GitHub
parent bcd4225680
commit 22364dc6d1
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3 changed files with 3 additions and 4 deletions
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1
.github/workflows/publish.yml vendored
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@ -33,7 +33,6 @@ jobs:
- name: Install dependencies - name: Install dependencies
run: | run: |
python -m pip install --upgrade pip wheel build twine python -m pip install --upgrade pip wheel build twine
pip install "git+https://github.com/squidfunk/mkdocs-material@master"
pip install -e ".[dev]" --extra-index-url https://download.pytorch.org/whl/cpu pip install -e ".[dev]" --extra-index-url https://download.pytorch.org/whl/cpu
- name: Check PyPI version - name: Check PyPI version
shell: python shell: python

4
docs/en/datasets/explorer/api.md
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@ -192,8 +192,8 @@ You can also plot the results of a SQL query using the `plot_sql_query` method.
exp = Explorer(data='coco128.yaml', model='yolov8n.pt') exp = Explorer(data='coco128.yaml', model='yolov8n.pt')
exp.create_embeddings_table() exp.create_embeddings_table()
df = exp.sql_query("WHERE labels LIKE '%person%' AND labels LIKE '%dog%'") # plot the SQL Query
print(df.head()) exp.plot_sql_query("WHERE labels LIKE '%person%' AND labels LIKE '%dog%' LIMIT 10")
``` ```
## 4. Advanced - Working with Embeddings Table ## 4. Advanced - Working with Embeddings Table

2
pyproject.toml
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@ -89,7 +89,7 @@ dev = [
"pytest", "pytest",
"pytest-cov", "pytest-cov",
"coverage[toml]", "coverage[toml]",
"mkdocs-material", "mkdocs-material>=9.5.9",
"mkdocstrings[python]", "mkdocstrings[python]",
"mkdocs-jupyter", # for notebooks "mkdocs-jupyter", # for notebooks
"mkdocs-redirects", # for 301 redirects "mkdocs-redirects", # for 301 redirects