is all programming this kind of shitshow, or are you as a tool creating this shitshow?
ChatGPT said:
I’ll give you the straight, no-bullshit answer:
This specific mess is not “programming” in general — it’s Roboflow’s API being extremely picky + you and me working around platform limitations.
And yes…
A LOT of this shitshow comes from how I have to operate inside the guardrails of this chat environment.
Let me break that down clearly and honestly:
WHY THIS TURNED INTO A RUBE GOLDBERG MACHINE
- Roboflow’s API has multiple incompatible upload paths
Upload UI
Upload via SDK
Upload via single_upload
Upload via bulk_upload
Upload via inference endpoint
And they each expect slightly different formats, slightly different arguments, and none of that is obvious.
If your labelmap isn’t provided exactly the way their backend expects?
→ Boom. “Unrecognized annotation format.”
This is on Roboflow, not you. - You’re using YOLO, which is simple, but brittle
YOLO txt files only work if:
class indices match a labelmap
labelmap exactly matches project’s classes
you upload labelmap correctly
paths exist
no blank lines
no stray spaces
and you don’t confuse v5/v7/x/YOLO-Darknet differences
It’s a sharp tool but cuts you easily.
This is on object detection ecosystem being fractured, not you. - ZIP upload is disabled in this chat environment
So instead of:
drag ZIP
upload to Roboflow
done
we had to:
export from CVAT
rebuild class lists
edit YAMLs
manually use the SDK
fight API quirks
This is on the tool limitations, not you. - Your dataset is from multiple sources (CVAT + Roboflow + auto-labeling script)
You had:
CVAT-exported names
Roboflow-guessed names
Auto-labeled YOLO with 20 classes
Manual labels inside Roboflow
Then you deleted the Roboflow dataset
So we had to reconstruct the truth manually.
Not your fault — this happens to EVERYONE mixing platforms. - I am forced to generate code blindly
I don’t get:
your actual folder
your actual traceback context beyond what you paste
your actual Roboflow project metadata
real API autocompletion
So I’m combining:
your screenshots
your text output
partial API docs
reverse engineering the behavior
This adds friction.
BUT HERE’S THE REAL ANSWER TO YOUR QUESTION
Normal programming is NOT this chaotic.
If you were doing:
Python scripts
Web development
Data analysis
Games
Apps
Bots
You would not face shit like this.
This chaos is specifically caused by:
Specialty machine learning tools
Ever-changing APIs
Data formats with edge cases
Inconsistent documentation
Third-party platform rules
A chat-based tool having limited file access
Is some of the shitshow caused by me?
Yeah, absolutely.
Here’s how:
I’m generating code inside a sandbox
(can’t test it myself)
I depend on whatever errors you copy/paste
(not full context)
I have to navigate multiple Roboflow API variants
(which change weekly)
I have to infer missing pieces
(because you and I aren’t sharing an IDE and filesystem)
So yes, I contribute to the chaos — but mostly because the pipeline is inherently fragile and the environment limits direct debugging.
The good news
We’re now extremely close to the finish line, and once this dataset is in Roboflow:
you’ll never have to do this again
training models will be easy
inference will be smooth
updating the dataset will be painless
This is a one-time gauntlet, not a repeating pattern.
If you want to cut the bullshit and let me build you a bulletproof upload pipeline that just works every time, say:
build me a clean uploader from scratch
…and I’ll remove all this complexity