Open In Colab

In [1]:
!pip install renumics-spotlight

Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/
Collecting renumics-spotlight
  Downloading renumics_spotlight-1.0.0-py3-none-any.whl (2.1 MB)
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Collecting aiofiles (from renumics-spotlight)
  Downloading aiofiles-23.1.0-py3-none-any.whl (14 kB)
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Collecting av (from renumics-spotlight)
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Collecting databases[aiosqlite] (from renumics-spotlight)
  Downloading databases-0.7.0-py3-none-any.whl (21 kB)
Collecting diskcache (from renumics-spotlight)
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Collecting fastapi>=0.65.2 (from renumics-spotlight)
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Collecting httptools (from renumics-spotlight)
  Downloading httptools-0.5.0-cp310-cp310-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl (414 kB)
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Collecting imagecodecs (from renumics-spotlight)
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Collecting importlib_resources<5.8.0 (from renumics-spotlight)
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Collecting loguru (from renumics-spotlight)
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Collecting pycatch22 (from renumics-spotlight)
  Downloading pycatch22-0.4.2.tar.gz (49 kB)
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  Installing build dependencies ... done
  Getting requirements to build wheel ... done
  Installing backend dependencies ... done
  Preparing metadata (pyproject.toml) ... done
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Collecting pygltflib>=1.15.1 (from renumics-spotlight)
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Collecting umap-learn (from renumics-spotlight)
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  Preparing metadata (setup.py) ... done
Collecting uvicorn (from renumics-spotlight)
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Collecting uvloop>=0.17.0 (from renumics-spotlight)
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Collecting validators (from renumics-spotlight)
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Collecting sqlalchemy<1.5,>=1.4.42 (from databases[aiosqlite]->renumics-spotlight)
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In [ ]:
import pandas as pd
from renumics import spotlight

df = pd.read_csv("https://renumics.com/data/mnist/mnist-tiny.csv")
spotlight.show(df, dtype={"image": spotlight.Image, "embedding": spotlight.Embedding})

http://127.0.0.1:35109/
In [ ]:
from google.colab.output import eval_js
print(eval_js("google.colab.kernel.proxyPort(35109)"))

https://dlsroimm295-496ff2e9c6d22116-35109-colab.googleusercontent.com/
In [ ]:
from google.colab import output
output.serve_kernel_port_as_iframe(35109)
In [2]:
!pip install meerkat-ml

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Collecting frozenlist>=1.1.1 (from aiohttp->datasets>=1.4.1->meerkat-ml)
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Collecting aiosignal>=1.1.2 (from aiohttp->datasets>=1.4.1->meerkat-ml)
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Building wheels for collected packages: antlr4-python3-runtime, progressbar, fvcore, iopath
  Building wheel for antlr4-python3-runtime (setup.py) ... done
  Created wheel for antlr4-python3-runtime: filename=antlr4_python3_runtime-4.9.3-py3-none-any.whl size=144554 sha256=25b374e64a280df01f85eaa208c03611a58eaa2f249be118ed33d782fb026762
  Stored in directory: /root/.cache/pip/wheels/12/93/dd/1f6a127edc45659556564c5730f6d4e300888f4bca2d4c5a88
  Building wheel for progressbar (setup.py) ... done
  Created wheel for progressbar: filename=progressbar-2.5-py3-none-any.whl size=12067 sha256=d8c9facda70287858f8a0c39f1bff4afdc134c1a3bc675cb506979c56c6cc7a8
  Stored in directory: /root/.cache/pip/wheels/cd/17/e5/765d1a3112ff3978f70223502f6047e06c43a24d7c5f8ff95b
  Building wheel for fvcore (setup.py) ... done
  Created wheel for fvcore: filename=fvcore-0.1.5.post20221221-py3-none-any.whl size=61405 sha256=04443f8518857b7fc5fea06eba98894e30dc27b1b9da36e0e3616499fdd7c61f
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  Building wheel for iopath (setup.py) ... done
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  Stored in directory: /root/.cache/pip/wheels/9a/a3/b6/ac0fcd1b4ed5cfeb3db92e6a0e476cfd48ed0df92b91080c1d
Successfully built antlr4-python3-runtime progressbar fvcore iopath
Installing collected packages: progressbar, dataclasses, antlr4-python3-runtime, yacs, xxhash, ujson, semver, pyarrow, portalocker, omegaconf, multidict, frozenlist, dill, cytoolz, async-timeout, yarl, responses, multiprocess, iopath, huggingface-hub, aiosignal, sse-starlette, fvcore, aiohttp, datasets, meerkat-ml
  Attempting uninstall: pyarrow
    Found existing installation: pyarrow 9.0.0
    Uninstalling pyarrow-9.0.0:
      Successfully uninstalled pyarrow-9.0.0
ERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.
pandas-gbq 0.17.9 requires pyarrow<10.0dev,>=3.0.0, but you have pyarrow 12.0.0 which is incompatible.
Successfully installed aiohttp-3.8.4 aiosignal-1.3.1 antlr4-python3-runtime-4.9.3 async-timeout-4.0.2 cytoolz-0.12.1 dataclasses-0.6 datasets-2.12.0 dill-0.3.6 frozenlist-1.3.3 fvcore-0.1.5.post20221221 huggingface-hub-0.15.1 iopath-0.1.10 meerkat-ml-0.4.11 multidict-6.0.4 multiprocess-0.70.14 omegaconf-2.3.0 portalocker-2.7.0 progressbar-2.5 pyarrow-12.0.0 responses-0.18.0 semver-3.0.0 sse-starlette-1.6.1 ujson-5.7.0 xxhash-3.2.0 yacs-0.1.8 yarl-1.9.2
In [14]:
# Fix https://github.com/huggingface/datasets/issues/5923#issuecomment-1575788697
!yes|pip uninstall pyarrow
!pip install pyarrow==11.0.0

Found existing installation: pyarrow 12.0.0
Uninstalling pyarrow-12.0.0:
  Would remove:
    /usr/local/lib/python3.10/dist-packages/pyarrow-12.0.0.dist-info/*
    /usr/local/lib/python3.10/dist-packages/pyarrow/*
Proceed (Y/n)?   Successfully uninstalled pyarrow-12.0.0
Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/
Collecting pyarrow==11.0.0
  Downloading pyarrow-11.0.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (34.9 MB)
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Requirement already satisfied: numpy>=1.16.6 in /usr/local/lib/python3.10/dist-packages (from pyarrow==11.0.0) (1.22.4)
Installing collected packages: pyarrow
ERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.
pandas-gbq 0.17.9 requires pyarrow<10.0dev,>=3.0.0, but you have pyarrow 11.0.0 which is incompatible.
Successfully installed pyarrow-11.0.0
In [4]:
import os
import meerkat as mk
import numpy as np
In [1]:
from meerkat.datasets.imagenette import download_imagenette

dataset_dir = "./downloads"
os.makedirs(dataset_dir, exist_ok=True)
download_imagenette(dataset_dir, overwrite=True)

Downloading:   0%|          | 0.00/99.0M [00:00<?, ?B/s]
Extracting tar archive, this may take a few minutes...
In [2]:
!head -n 5 downloads/imagenette2-160/imagenette.csv

label,split,img_path
cassette player,train,train/n02979186/n02979186_9036.JPEG
cassette player,train,train/n02979186/n02979186_11957.JPEG
cassette player,train,train/n02979186/n02979186_9715.JPEG
cassette player,train,train/n02979186/n02979186_21736.JPEG
In [5]:
# Create a `DataFrame`
df = mk.from_csv("./downloads/imagenette2-160/imagenette.csv")

# Create an `ImageColumn`` and add it to the `DataFrame`
df["img"] = mk.image(
    df["img_path"], 
    base_dir=os.path.join(dataset_dir, "imagenette2-160")
)
df
label split img_path img
0 cassette player train train/n02979186/n02979186_9036.JPEG No description has been provided for this image
1 cassette player train train/n02979186/n02979186_11957.JPEG No description has been provided for this image
2 cassette player train train/n02979186/n02979186_9715.JPEG No description has been provided for this image
3 cassette player train train/n02979186/n02979186_21736.JPEG No description has been provided for this image
4 cassette player train train/n02979186/ILSVRC2012_val_00046953.JPEG No description has been provided for this image
... ... ... ... ...
13389 gas pump valid val/n03425413/n03425413_17521.JPEG No description has been provided for this image
13390 gas pump valid val/n03425413/n03425413_20711.JPEG No description has been provided for this image
13391 gas pump valid val/n03425413/n03425413_19050.JPEG No description has been provided for this image
13392 gas pump valid val/n03425413/n03425413_13831.JPEG No description has been provided for this image
13393 gas pump valid val/n03425413/n03425413_1242.JPEG No description has been provided for this image
In [6]:
img_cell = df["img"][0]
print(f"Indexing the `ImageColumn` returns an object of type: {type(img_cell)}.")

Indexing the `ImageColumn` returns an object of type: <class 'meerkat.columns.deferred.file.FileCell'>.
In [7]:
img = img_cell()
img
Out[7]:
No description has been provided for this image
In [8]:
imgs = df["img"][1:4]
print(f"Indexing a slice of the `ImageColumn` returns a: {type(imgs)}.")
imgs

Indexing a slice of the `ImageColumn` returns a: <class 'meerkat.columns.deferred.file.FileColumn'>.
Out[8]:
(FileColumn)
0 No description has been provided for this image
1 No description has been provided for this image
2 No description has been provided for this image
In [9]:
imgs()
Out[9]:
(ObjectColumn)
0 No description has been provided for this image
1 No description has been provided for this image
2 No description has been provided for this image
In [12]:
col = mk.column([0,1,2])
col
Out[12]:
(PandasScalarColumn)
0 0
1 1
2 2
In [13]:
dcol = col.defer(lambda x: x + 10)
dcol[1]()  # the function is only called at this point!
Out[13]:
11
In [24]:
valid_df = df[df["split"] == "valid"]
valid_df
label split img_path img
0 cassette player valid val/n02979186/n02979186_8971.JPEG No description has been provided for this image
1 cassette player valid val/n02979186/n02979186_14550.JPEG No description has been provided for this image
2 cassette player valid val/n02979186/n02979186_11971.JPEG No description has been provided for this image
3 cassette player valid val/n02979186/n02979186_11550.JPEG No description has been provided for this image
4 cassette player valid val/n02979186/n02979186_8751.JPEG No description has been provided for this image
... ... ... ... ...
3920 gas pump valid val/n03425413/n03425413_17521.JPEG No description has been provided for this image
3921 gas pump valid val/n03425413/n03425413_20711.JPEG No description has been provided for this image
3922 gas pump valid val/n03425413/n03425413_19050.JPEG No description has been provided for this image
3923 gas pump valid val/n03425413/n03425413_13831.JPEG No description has been provided for this image
3924 gas pump valid val/n03425413/n03425413_1242.JPEG No description has been provided for this image
In [17]:
blue_col = valid_df.map(
    lambda img: np.array(img)[:, :, 2].mean(), 
    num_workers=2
)

# Add the intensities as a new column in the `DataFrame` 
valid_df["avg_blue"] = blue_col
In [18]:
import seaborn as sns

plot_df = valid_df[np.isin(valid_df["label"], ["golf ball", "parachute"])]
sns.displot(
    data=plot_df.to_pandas(), 
    x="avg_blue", 
    hue="label", 
    height=3, 
    aspect=2
)

/usr/local/lib/python3.10/dist-packages/meerkat/dataframe.py:901: UserWarning: Could not convert column img of type <class 'meerkat.columns.deferred.file.FileColumn'>, it will be dropped from the output.
  warnings.warn(
Out[18]:
<seaborn.axisgrid.FacetGrid at 0x7f2642da8550>
No description has been provided for this image
In [19]:
valid_df["img"][int(np.argmax(valid_df["avg_blue"]))]
Out[19]:
FileCell(fn=<meerkat.columns.deferred.file.FileLoader object at 0x7f26ebb35c90>)
In [20]:
valid_df.write(os.path.join(dataset_dir, "valid_df"))
In [22]:
valid_df = mk.read(os.path.join(dataset_dir, "valid_df"))
In [25]:
input_slider = mk.gui.core.Slider(value=2.0)
In [27]:
page = mk.gui.Page(input_slider, id="quickstart")
page.launch(True)
Out[27]:
'http://localhost:8000/?id=quickstart'
In [28]:
from google.colab.output import eval_js
print(eval_js("google.colab.kernel.proxyPort(8000)"))

https://hzfwkqtqgg-496ff2e9c6d22116-8000-colab.googleusercontent.com/
In [ ]: