Spaces:
Sleeping
Sleeping
| """Pixel-to-inch calibration using the conveyor belt as a known reference. | |
| The 30" belt width is mapped to the image HEIGHT (in pixels), not image | |
| width. This matches the camera setup where the 30" cross-belt dimension | |
| corresponds to the shorter side of the cropped region of interest. | |
| """ | |
| from __future__ import annotations | |
| import pandas as pd | |
| BELT_WIDTH_IN_DEFAULT = 30.0 | |
| def apply_real_scale(df: pd.DataFrame, belt_width_in: float = BELT_WIDTH_IN_DEFAULT) -> pd.DataFrame: | |
| """Add real-scale columns derived from belt-width calibration. | |
| Adds: width_in, height_in, inMinDim, area_poly_in2. | |
| Expects columns: img_height_px, width_px, height_px, area_poly_px. | |
| """ | |
| df = df.copy() | |
| inch_per_px = belt_width_in / df["img_height_px"] | |
| scale_area_in2 = inch_per_px**2 | |
| df["width_in"] = df["width_px"] * inch_per_px | |
| df["height_in"] = df["height_px"] * inch_per_px | |
| df["inMinDim"] = df[["width_in", "height_in"]].min(axis=1) | |
| df["area_poly_in2"] = df["area_poly_px"] * scale_area_in2 | |
| return df | |