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Docs updates: Add Explorer to tab, YOLOv5 in Guides and Usage in Quickstart (#7438)

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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: Haixuan Xavier Tao <tao.xavier@outlook.com>
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Ayush Chaurasia 2024-01-10 04:20:26 +05:30 • committed by GitHub
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39
ultralytics/data/explorer/explorer.py
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@ -1,3 +1,5 @@
# Ultralytics YOLO 🚀, AGPL-3.0 license
from io import BytesIO
from pathlib import Path
from typing import Any, List, Tuple, Union
@ -24,9 +26,8 @@ class ExplorerDataset(YOLODataset):
def __init__(self, *args, data: dict = None, **kwargs) -> None:
super().__init__(*args, data=data, **kwargs)
# NOTE: Load the image directly without any resize operations.
def load_image(self, i: int) -> Union[Tuple[np.ndarray, Tuple[int, int], Tuple[int, int]], Tuple[None, None, None]]:
"""Loads 1 image from dataset index 'i', returns (im, resized hw)."""
"""Loads 1 image from dataset index 'i' without any resize ops."""
im, f, fn = self.ims[i], self.im_files[i], self.npy_files[i]
if im is None: # not cached in RAM
if fn.exists(): # load npy
@ -41,6 +42,7 @@ class ExplorerDataset(YOLODataset):
return self.ims[i], self.im_hw0[i], self.im_hw[i]
def build_transforms(self, hyp: IterableSimpleNamespace = None):
"""Creates transforms for dataset images without resizing."""
return Format(
bbox_format='xyxy',
normalize=False,
@ -122,7 +124,7 @@ class Explorer:
self.table = table
def _yield_batches(self, dataset: ExplorerDataset, data_info: dict, model: YOLO, exclude_keys: List[str]):
# Implement Batching
"""Generates batches of data for embedding, excluding specified keys."""
for i in tqdm(range(len(dataset))):
self.progress = float(i + 1) / len(dataset)
batch = dataset[i]
@ -143,7 +145,7 @@ class Explorer:
limit (int): Number of results to return.
Returns:
An arrow table containing the results. Supports converting to:
(pyarrow.Table): An arrow table containing the results. Supports converting to:
- pandas dataframe: `result.to_pandas()`
- dict of lists: `result.to_pydict()`
@ -175,7 +177,7 @@ class Explorer:
return_type (str): Type of the result to return. Can be either 'pandas' or 'arrow'. Defaults to 'pandas'.
Returns:
An arrow table containing the results.
(pyarrow.Table): An arrow table containing the results.
Example:
```python
@ -216,7 +218,7 @@ class Explorer:
labels (bool): Whether to plot the labels or not.
Returns:
PIL Image containing the plot.
(PIL.Image): Image containing the plot.
Example:
```python
@ -248,7 +250,7 @@ class Explorer:
return_type (str): Type of the result to return. Can be either 'pandas' or 'arrow'. Defaults to 'pandas'.
Returns:
A table or pandas dataframe containing the results.
(pandas.DataFrame): A dataframe containing the results.
Example:
```python
@ -282,7 +284,7 @@ class Explorer:
limit (int): Number of results to return. Defaults to 25.
Returns:
PIL Image containing the plot.
(PIL.Image): Image containing the plot.
Example:
```python
@ -306,11 +308,12 @@ class Explorer:
Args:
max_dist (float): maximum L2 distance between the embeddings to consider. Defaults to 0.2.
top_k (float): Percentage of the closest data points to consider when counting. Used to apply limit when running
vector search. Defaults: None.
vector search. Defaults: None.
force (bool): Whether to overwrite the existing similarity index or not. Defaults to True.
Returns:
A pandas dataframe containing the similarity index.
(pandas.DataFrame): A dataframe containing the similarity index. Each row corresponds to an image, and columns
include indices of similar images and their respective distances.
Example:
```python
@ -340,6 +343,7 @@ class Explorer:
sim_table = self.connection.create_table(sim_idx_table_name, schema=get_sim_index_schema(), mode='overwrite')
def _yield_sim_idx():
"""Generates a dataframe with similarity indices and distances for images."""
for i in tqdm(range(len(embeddings))):
sim_idx = self.table.search(embeddings[i]).limit(top_k).to_pandas().query(f'_distance <= {max_dist}')
yield [{
@ -364,7 +368,7 @@ class Explorer:
force (bool): Whether to overwrite the existing similarity index or not. Defaults to True.
Returns:
PIL.PngImagePlugin.PngImageFile containing the plot.
(PIL.Image): Image containing the plot.
Example:
```python
@ -416,7 +420,7 @@ class Explorer:
query (str): Question to ask.
Returns:
Answer from AI.
(pandas.DataFrame): A dataframe containing filtered results to the SQL query.
Example:
```python
@ -436,14 +440,17 @@ class Explorer:
def visualize(self, result):
"""
Visualize the results of a query.
Visualize the results of a query. TODO.
Args:
result (arrow table): Arrow table containing the results of a query.
result (pyarrow.Table): Table containing the results of a query.
"""
# TODO:
pass
def generate_report(self, result):
"""Generate a report of the dataset."""
"""
Generate a report of the dataset.
TODO
"""
pass