PyCharm Code and Docs Inspect fixes v1

[RizwanMunawar]

🛠️ PR Summary

_{Made with ❤️ by Ultralytics Actions}

🌟 Summary

This PR significantly improves documentation consistency and code clarity across the repository by fixing typos, updating explanations, and standardizing naming conventions.

📊 Key Changes

• Documentation Fixes:

  • Corrected grammatical errors, improved phrasing, and made descriptions clearer in multiple documentation files (e.g., SKU-110k, NVIDIA Jetson, Tiled Inference, and others).
  • Updated markdown formatting to align with modern best practices, such as replacing deprecated warning styles with proper context labels (!!! warning blocks).

• Code Style Updates:

  • Renamed methods and variables for better readability and adherence to naming conventions (e.g., applyEcc → applyecc, coords → coordinates, smooth_BCE → smooth_bce).
  • Refactored a large configuration initialization block for compactness and ease of readability.

• Code Examples:

  • Improved Python code snippets in docs and code comments for correctness and clarity.

• Typographical Consistency:

  • Standardized terms like "multiscale" (replacing inconsistent variations like "multi-scale") and ensured uniform phrasing in parameter descriptions across files.

🎯 Purpose & Impact

• Purpose:

  • To enhance developer and user experience by making documentation and code more understandable.
  • To align code with internal style guides and best programming practices.

• Impact on Users:

  • Easier navigation and implementation for new users thanks to clearer instructions and corrected examples.
  • More maintainable and consistent naming conventions for developers, reducing confusion.

• Impact on Codebase:

  • Cleaner and more readable code improves collaboration and minimizes onboarding time for contributors.

[UltralyticsAssistant]

👋 Hello @RizwanMunawar, thank you for submitting an ultralytics/ultralytics 🚀 PR! To ensure a seamless integration of your work, please review the following checklist:

• ✅ Define a Purpose: Clearly explain the purpose of your fix or feature in your PR description. Ensure your commit messages are clear, concise, and adhere to the project's conventions.
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[codecov]

Codecov Report

Attention: Patch coverage is 70.00000% with 3 lines in your changes missing coverage. Please review.

Project coverage is 73.79%. Comparing base (126867e) to head (06bfef1).
Report is 4 commits behind head on main.

Files with missing lines	Patch %	Lines
ultralytics/data/augment.py	0.00%	2 Missing ⚠️
ultralytics/models/sam/predict.py	0.00%	1 Missing ⚠️

Additional details and impacted files

@@            Coverage Diff             @@
##             main   #18461      +/-   ##
==========================================
+ Coverage   73.70%   73.79%   +0.09%     
==========================================
  Files         129      129              
  Lines       17280    17267      -13     
==========================================
+ Hits        12736    12742       +6     
+ Misses       4544     4525      -19     

Flag	Coverage Δ
Benchmarks	34.91% <10.00%> (+0.06%)	⬆️
GPU	38.32% <10.00%> (+0.02%)	⬆️
Tests	67.57% <70.00%> (+0.05%)	⬆️

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[RizwanMunawar]

@glenn-jocher Hi, could you please review this PR? Let me know if any changes are needed, and I can update things accordingly. Thank you!

@Laughing-q Hey buddy, I’ve updated the SAM/predict.py structure of the inference_state dictionary as outlined below, this will resolve the warning that PyCharm was throwing. Can you please review this? Thank you!

inference_state = {
  "num_frames": predictor.dataset.frames,
  "point_inputs_per_obj": {},
  "mask_inputs_per_obj": {},
  "constants": {},
  "obj_id_to_idx": OrderedDict(),
  "obj_idx_to_id": OrderedDict(),
  "obj_ids": [],
  "output_dict": {
      "cond_frame_outputs": {},  # dict containing {frame_idx: <out>}
      "non_cond_frame_outputs": {},  # dict containing {frame_idx: <out>}
  },
  "output_dict_per_obj": {},
  "temp_output_dict_per_obj": {},
  "consolidated_frame_inds": {
      "cond_frame_outputs": set(),  # set containing frame indices
      "non_cond_frame_outputs": set(),  # set containing frame indices
  },
  "tracking_has_started": False,
  "frames_already_tracked": [],
}
predictor.inference_state = inference_state