[Docs] Update install tutorial.

[mzr1996]

Motivation

The original tutorial introduced mim, mmengine, and mmcv before installing mmclassification.

But most are unnecessary, and we can compress the entire install procedure into one lines (package mode)

pip install openmim && mim install "mmcls>=1.0.0rc0"

and three lines (dev mode)

git clone -b 1.x https://github.com/open-mmlab/mmclassification.git
cd mmclassification
pip install openmim && mim install -e .

BC-breaking (Optional)

Does the modification introduce changes that break the backward compatibility of the downstream repositories?
If so, please describe how it breaks the compatibility and how the downstream projects should modify their code to keep compatibility with this PR.

Use cases (Optional)

If this PR introduces a new feature, it is better to list some use cases here and update the documentation.

Checklist

Before PR:

• Pre-commit or other linting tools are used to fix the potential lint issues.
• Bug fixes are fully covered by unit tests, the case that causes the bug should be added in the unit tests.
• The modification is covered by complete unit tests. If not, please add more unit test to ensure the correctness.
• The documentation has been modified accordingly, like docstring or example tutorials.

After PR:

• If the modification has potential influence on downstream or other related projects, this PR should be tested with those projects, like MMDet or MMSeg.
• CLA has been signed and all committers have signed the CLA in this PR.

[codecov]

Codecov Report

Base: 0.02% // Head: 89.05% // Increases project coverage by +89.03% 🎉

Coverage data is based on head (0628e96) compared to base (e8284a4).
Patch has no changes to coverable lines.

❗ Current head 0628e96 differs from pull request most recent head 9acfd01. Consider uploading reports for the commit 9acfd01 to get more accurate results

Additional details and impacted files

@@            Coverage Diff             @@
##             1.x    #1223       +/-   ##
==========================================
+ Coverage   0.02%   89.05%   +89.03%     
==========================================
  Files        121      147       +26     
  Lines       8239    11205     +2966     
  Branches    1371     1777      +406     
==========================================
+ Hits           2     9979     +9977     
+ Misses      8237      975     -7262     
- Partials       0      251      +251     

Flag	Coverage Δ
unittests	89.05% <ø> (+89.03%)	⬆️

Flags with carried forward coverage won't be shown. Click here to find out more.

Impacted Files	Coverage Δ
mmcls/apis/inference.py	0.00% <0.00%> (ø)
mmcls/data/cls_data_sample.py
mmcls/datasets/pipelines/__init__.py
mmcls/data/__init__.py
mmcls/datasets/pipelines/processing.py
mmcls/datasets/pipelines/compose.py
mmcls/datasets/pipelines/auto_augment.py
mmcls/datasets/pipelines/formatting.py
mmcls/models/classifiers/hugging_face.py	25.33% <0.00%> (ø)
mmcls/engine/hooks/margin_head_hooks.py	92.59% <0.00%> (ø)
... and 143 more

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[tonysy]

LGTM