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#!/usr/bin/env python3
"""
Quick debug script to test model locally and inspect detections
Run this in your container or locally to see what the model returns
"""
import os
os.environ["CUDA_VISIBLE_DEVICES"] = ""
from PIL import Image
import numpy as np
from rfdetr import RFDETRSegPreview
import supervision as sv
# Path to your checkpoint
CHECKPOINT_PATH = "/tmp/checkpoint_best_total.pth"
print("Loading model...")
model = RFDETRSegPreview(pretrain_weights=CHECKPOINT_PATH)
print("Model loaded!")
# Create a test image (or load your own)
test_img = Image.new("RGB", (640, 480), color=(73, 109, 137))
print(f"Test image size: {test_img.size}")
# Run prediction
print("\nRunning prediction with threshold=0.25...")
detections = model.predict(test_img, threshold=0.25)
print("\n" + "="*60)
print("DETECTION RESULTS:")
print("="*60)
print(f"Type: {type(detections)}")
print(f"Length: {len(detections)}")
# Check attributes
attrs = dir(detections)
print(f"\nAvailable attributes: {[a for a in attrs if not a.startswith('_')]}")
if hasattr(detections, 'confidence'):
print(f"\nConfidence scores: {detections.confidence}")
print(f"Confidence count: {len(detections.confidence)}")
print(f"Confidence type: {type(detections.confidence)}")
if hasattr(detections, 'class_id'):
print(f"\nClass IDs: {detections.class_id}")
print(f"Class count: {len(detections.class_id)}")
if hasattr(detections, 'masks'):
masks = detections.masks
print(f"\nMasks present: {masks is not None}")
if masks is not None:
print(f"Masks type: {type(masks)}")
if hasattr(masks, 'shape'):
print(f"Masks shape: {masks.shape}")
elif hasattr(masks, '__len__'):
print(f"Masks length: {len(masks)}")
if len(masks) > 0:
print(f"First mask type: {type(masks[0])}")
if hasattr(masks[0], 'shape'):
print(f"First mask shape: {masks[0].shape}")
else:
print("\nNO MASKS ATTRIBUTE FOUND!")
# Try to annotate
if len(detections) > 0:
print("\n" + "="*60)
print("Testing annotation...")
print("="*60)
try:
palette = sv.ColorPalette.from_hex(["#ffff00", "#ff9b00"])
mask_annotator = sv.MaskAnnotator(color=palette)
annotated = mask_annotator.annotate(test_img, detections)
print("✓ Mask annotation successful!")
print(f"Annotated image size: {annotated.size}")
except Exception as e:
print(f"✗ Mask annotation failed: {e}")
import traceback
traceback.print_exc()
print("\n" + "="*60)
print("Debug complete!")
print("="*60) |