[Bug] RT-DETR post-processing yields incorrect results when use_focal_loss=False
Author: dwchoo
Pull request: no
Labels: name: bug

name: Vision

### System Info

- `transformers` version: 4.45.0.dev0
- Platform: Linux-5.19.0-1010-nvidia-lowlatency-x86_64-with-glibc2.35
- Python version: 3.10.12
- Huggingface_hub version: 0.24.5
- Safetensors version: 0.4.4
- Accelerate version: 0.33.0
- Accelerate config:    not found
- PyTorch version (GPU?): 2.4.0a0+07cecf4168.nv24.05 (True)
- Tensorflow version (GPU?): not installed (NA)
- Flax version (CPU?/GPU?/TPU?): not installed (NA)
- Jax version: not installed
- JaxLib version: not installed
- Using distributed or parallel set-up in script?: <fill in>
- Using GPU in script?: <fill in>
- GPU type: NVIDIA GeForce RTX 4090

### Who can help?

@amyeroberts

### Information

- [X] The official example scripts
- [ ] My own modified scripts

### Tasks

- [ ] An officially supported task in the `examples` folder (such as GLUE/SQuAD, ...)
- [X] My own task or dataset (give details below)

### Reproduction

The official usage [example](https://huggingface.co/docs/transformers/model_doc/rt_detr#usage-tips) for RT-DETR in the documentation produces incorrect results when `use_focal_loss` is set to `False` in the `post_process_object_detection` method.
```python
import torch
import requests

from PIL import Image
from transformers import RTDetrForObjectDetection, RTDetrImageProcessor

url = 'http://images.cocodataset.org/val2017/000000039769.jpg' 
image = Image.open(requests.get(url, stream=True).raw)

image_processor = RTDetrImageProcessor.from_pretrained("PekingU/rtdetr_r50vd")
model = RTDetrForObjectDetection.from_pretrained("PekingU/rtdetr_r50vd")

inputs = image_processor(images=image, return_tensors="pt")

with torch.no_grad():
    outputs = model(**inputs)

# Here is changed
# Default use_focal_loss=True
results = image_processor.post_process_object_detection(outputs, target_sizes=torch.tensor([image.size[::-1]]), threshold=0.3, use_focal_loss=False) 

for result in results:
    for score, label_id, box in zip(result["scores"], result["labels"], result["boxes"]):
        score, label = score.item(), label_id.item()
        box = [round(i, 2) for i in box.tolist()]
        print(f"{model.config.id2label[label]}: {score:.2f} {box}")
```

### Expected behavior

### When `use_focal_loss=True`
```
sofa: 0.97 [0.14, 0.38, 640.13, 476.21]
cat: 0.96 [343.38, 24.28, 640.14, 371.5]
cat: 0.96 [13.23, 54.18, 318.98, 472.22]
remote: 0.95 [40.11, 73.44, 175.96, 118.48]
remote: 0.92 [333.73, 76.58, 369.97, 186.99]
```
![true](https://github.com/user-attachments/assets/5618b5d2-995e-4554-ae1b-e42e4f9b652f)


### When `use_focal_loss=False`
```
person: 1.00 [40.11, 73.44, 175.96, 118.48]
person: 1.00 [343.38, 24.28, 640.14, 371.5]
person: 1.00 [13.23, 54.18, 318.98, 472.22]
person: 1.00 [333.73, 76.58, 369.97, 186.99]
person: 1.00 [-10.18, -66.86, 629.35, 412.62]
person: 1.00 [0.85, -69.13, 640.82, 410.67]
person: 1.00 [4.19, -24.31, 644.17, 378.63]
person: 1.00 [0.04, -62.35, 640.01, 417.49]
person: 1.00 [-8.1, 136.34, 631.0, 385.72]
person: 1.00 [11.32, 54.2, 317.21, 473.39]
person: 1.00 [-5.81, 139.17, 620.73, 380.67]
person: 1.00 [2.41, 18.83, 642.39, 378.26]
person: 1.00 [-9.84, 21.47, 629.93, 322.49]
person: 1.00 [0.36, -1.19, 640.35, 478.7]
person: 1.00 [-44.53, -104.03, 595.36, 373.99]
person: 1.00 [0.91, -39.17, 640.89, 440.75]
person: 1.00 [-2.88, 216.51, 637.06, 434.71]
person: 1.00 [1.13, -0.58, 331.65, 476.0]
person: 1.00 [1.15, 58.44, 428.54, 471.67]
person: 1.00 [5.91, -66.87, 645.79, 378.84]
person: 1.00 [0.9, -44.8, 640.88, 435.03]
person: 1.00 [-0.19, -1.78, 639.8, 476.89]
person: 1.00 [1.72, 39.05, 641.1, 472.89]
person: 1.00 [343.53, 24.69, 639.36, 370.48]
person: 1.00 [1.8, 30.17, 640.73, 470.69]
person: 1.00 [6.8, -69.75, 646.77, 389.73]
person: 1.00 [0.6, 3.42, 640.59, 389.43]
person: 1.00 [-45.64, -107.19, 594.27, 372.2]
person: 1.00 [0.68, 0.79, 640.59, 314.32]
person: 1.00 [1.17, 1.47, 641.16, 384.91]
person: 1.00 [0.14, 0.38, 640.13, 476.21]
person: 1.00 [15.19, 6.0, 655.03, 271.6]
person: 1.00 [-35.92, -98.61, 602.61, 379.19]
person: 1.00 [1.21, -27.17, 641.2, 452.78]
person: 1.00 [-42.0, -93.72, 597.85, 385.56]
person: 1.00 [11.33, 127.73, 481.84, 470.83]
person: 1.00 [0.78, 2.29, 640.77, 375.53]
person: 1.00 [-38.3, -109.69, 599.97, 369.88]
person: 1.00 [-8.05, 198.77, 631.16, 385.42]
person: 1.00 [28.85, 277.41, 638.55, 475.06]
person: 1.00 [1.96, 262.19, 641.8, 475.22]
person: 1.00 [0.15, 234.33, 639.66, 465.15]
person: 1.00 [100.86, 25.73, 590.97, 369.99]
person: 1.00 [16.91, -39.15, 198.13, 427.58]
person: 1.00 [8.48, 56.71, 317.32, 377.75]
person: 1.00 [-24.16, 44.59, 609.98, 324.35]
person: 1.00 [1.67, -21.88, 641.65, 457.15]
person: 1.00 [1.58, 47.78, 263.77, 316.35]
person: 1.00 [66.05, 40.36, 641.24, 475.55]
person: 1.00 [8.08, 34.69, 559.91, 368.08]
person: 1.00 [0.03, 9.21, 185.75, 465.75]
person: 1.00 [0.51, 3.66, 640.51, 381.63]
person: 1.00 [-39.93, -109.05, 600.01, 370.51]
person: 1.00 [69.6, 72.99, 172.19, 112.08]
person: 1.00 [-38.78, -102.11, 600.59, 370.73]
person: 1.00 [59.02, 29.3, 615.04, 463.61]
person: 1.00 [37.15, 53.98, 308.09, 124.21]
person: 1.00 [1.09, 221.75, 638.09, 448.28]
person: 1.00 [-56.47, 27.89, 419.31, 455.42]
person: 1.00 [0.78, -0.79, 217.89, 478.34]
person: 1.00 [8.94, 25.11, 638.34, 472.57]
person: 1.00 [18.73, 35.29, 619.38, 458.91]
person: 1.00 [345.32, 23.68, 645.02, 269.5]
person: 1.00 [28.8, -47.42, 631.41, 350.5]
person: 1.00 [1.26, 42.63, 172.07, 298.25]
person: 1.00 [-12.0, -0.47, 598.94, 346.74]
person: 1.00 [-5.09, 173.18, 617.97, 383.35]
person: 1.00 [1.47, -0.27, 641.42, 415.41]
person: 1.00 [56.78, 13.05, 640.34, 473.68]
person: 1.00 [0.19, 0.81, 640.18, 130.65]
person: 1.00 [73.93, 121.67, 637.92, 474.11]
person: 1.00 [1.52, 72.09, 329.32, 478.16]
person: 1.00 [-8.07, -74.78, 594.32, 387.01]
person: 1.00 [19.6, -17.51, 635.97, 320.83]
person: 1.00 [-40.61, -73.53, 599.33, 371.17]
person: 1.00 [243.94, 26.74, 594.06, 309.69]
person: 1.00 [446.15, 18.67, 581.79, 310.19]
person: 1.00 [4.56, 285.25, 644.46, 469.4]
person: 1.00 [151.32, 62.36, 367.71, 326.84]
person: 1.00 [25.66, 283.26, 322.72, 474.62]
person: 1.00 [3.91, -25.77, 643.89, 399.53]
person: 1.00 [0.46, 191.1, 225.5, 458.27]
person: 1.00 [1.85, -17.32, 641.01, 460.72]
person: 1.00 [162.58, 50.65, 598.12, 381.86]
person: 1.00 [0.65, 236.97, 640.58, 449.68]
person: 1.00 [528.98, -1.92, 638.65, 62.44]
person: 1.00 [363.64, -0.13, 638.31, 82.46]
person: 1.00 [41.2, 73.73, 175.34, 118.12]
person: 1.00 [0.97, -1.93, 367.2, 477.25]
person: 1.00 [487.96, -0.82, 639.21, 82.64]
person: 1.00 [2.84, 37.55, 363.03, 340.35]
person: 1.00 [1.45, 331.03, 641.42, 476.01]
person: 1.00 [3.64, 66.66, 353.08, 363.45]
person: 1.00 [346.94, 25.13, 639.3, 471.17]
person: 1.00 [-0.81, -1.63, 336.41, 478.3]
person: 1.00 [11.35, 60.53, 399.96, 474.83]
person: 1.00 [202.02, 56.34, 609.75, 367.46]
person: 1.00 [64.17, 301.09, 637.44, 475.32]
person: 1.00 [43.04, 40.22, 549.0, 324.92]
person: 1.00 [0.49, 0.75, 639.51, 123.66]
person: 1.00 [2.91, 1.34, 496.53, 247.87]
person: 1.00 [-43.47, -95.43, 596.13, 383.73]
person: 1.00 [-0.32, 0.54, 639.64, 121.65]
person: 1.00 [2.36, 1.03, 480.97, 123.27]
person: 1.00 [1.69, 101.47, 625.26, 384.55]
person: 1.00 [10.54, 169.03, 224.0, 460.98]
person: 1.00 [-2.45, 46.63, 371.29, 441.16]
person: 1.00 [-25.4, -99.08, 593.66, 379.06]
person: 1.00 [490.38, 20.15, 639.81, 471.27]
person: 1.00 [1.95, 2.5, 641.92, 319.84]
person: 1.00 [0.54, 0.91, 640.43, 125.01]
person: 1.00 [1.31, 130.35, 121.19, 469.66]
person: 1.00 [-0.02, 0.68, 639.98, 124.31]
person: 1.00 [344.29, 93.63, 576.88, 370.13]
person: 1.00 [0.48, 37.4, 94.03, 470.18]
person: 1.00 [71.13, -0.23, 639.15, 81.83]
person: 1.00 [367.52, 37.94, 601.49, 230.9]
person: 1.00 [-30.56, -102.78, 600.38, 376.28]
person: 1.00 [5.34, 269.57, 643.09, 465.62]
person: 1.00 [369.59, -0.1, 638.84, 72.72]
person: 1.00 [173.63, 34.99, 579.36, 436.05]
person: 1.00 [11.33, 25.64, 638.05, 424.99]
person: 1.00 [4.19, 23.88, 644.11, 387.04]
person: 1.00 [-0.95, -73.24, 637.02, 368.35]
person: 1.00 [336.04, 77.28, 372.21, 257.29]
person: 1.00 [14.94, -66.54, 647.64, 379.76]
person: 1.00 [6.49, 132.64, 303.64, 466.5]
person: 1.00 [223.85, 45.22, 607.61, 361.32]
person: 1.00 [1.19, 0.52, 640.01, 122.91]
person: 1.00 [12.19, 69.9, 319.91, 312.88]
person: 1.00 [7.95, 7.4, 646.76, 442.46]
person: 1.00 [2.6, -38.88, 642.58, 440.3]
person: 1.00 [2.97, 127.14, 640.23, 475.11]
person: 1.00 [4.5, 94.64, 311.44, 313.71]
person: 1.00 [-0.41, -0.06, 639.58, 313.42]
person: 1.00 [17.37, 57.79, 215.01, 412.27]
person: 1.00 [10.01, 50.71, 269.38, 446.99]
person: 1.00 [-37.33, -48.81, 601.75, 404.09]
person: 1.00 [492.12, -0.21, 639.69, 70.05]
person: 1.00 [-21.18, -73.4, 590.9, 401.15]
person: 1.00 [408.74, 24.02, 643.94, 265.61]
person: 1.00 [17.23, 186.59, 247.22, 472.83]
person: 1.00 [151.44, 190.11, 297.58, 321.04]
person: 1.00 [3.88, 302.06, 643.83, 475.11]
person: 1.00 [0.27, 0.25, 640.26, 123.1]
person: 1.00 [492.85, 16.35, 640.26, 471.57]
person: 1.00 [14.62, 55.53, 316.26, 291.06]
person: 1.00 [14.1, -0.33, 631.16, 74.81]
person: 1.00 [334.63, 78.56, 470.02, 356.54]
person: 1.00 [3.77, 18.34, 479.68, 473.46]
person: 1.00 [344.6, 102.96, 638.63, 470.47]
person: 1.00 [2.75, 8.23, 640.96, 339.47]
person: 1.00 [108.61, 17.33, 635.49, 368.47]
person: 1.00 [487.9, -0.24, 638.91, 461.87]
person: 1.00 [158.74, 117.42, 639.63, 473.97]
person: 1.00 [1.58, 19.88, 305.79, 360.04]
person: 1.00 [498.59, 28.67, 640.16, 472.73]
person: 1.00 [-2.19, 201.11, 637.61, 382.93]
person: 1.00 [0.14, 49.01, 71.28, 435.95]
person: 1.00 [-15.64, 102.72, 604.85, 368.72]
person: 1.00 [494.15, 32.05, 628.72, 340.45]
person: 1.00 [1.41, 0.66, 639.71, 297.89]
person: 1.00 [2.69, 14.26, 640.87, 388.07]
person: 1.00 [340.11, 0.93, 638.18, 194.54]
person: 1.00 [0.94, 0.74, 639.67, 124.13]
person: 1.00 [0.18, 0.32, 640.17, 122.62]
person: 1.00 [500.6, 6.68, 639.57, 471.04]
person: 1.00 [348.77, 204.83, 628.61, 413.85]
person: 1.00 [-37.45, -96.32, 599.52, 380.37]
person: 1.00 [346.7, 93.69, 578.03, 370.37]
person: 1.00 [7.68, 56.58, 318.09, 370.17]
person: 1.00 [-39.59, -92.42, 598.33, 386.99]
person: 1.00 [1.42, 59.61, 315.34, 474.65]
person: 1.00 [7.24, -22.12, 645.44, 405.42]
person: 1.00 [148.65, 51.8, 632.96, 372.74]
person: 1.00 [7.99, 57.89, 427.42, 468.69]
person: 1.00 [256.47, 53.29, 602.2, 369.29]
person: 1.00 [417.25, 45.64, 579.57, 289.73]
person: 1.00 [8.96, 218.43, 623.48, 375.79]
person: 1.00 [345.58, 24.0, 640.83, 212.95]
person: 1.00 [2.6, 196.52, 221.6, 472.77]
person: 1.00 [1.54, -0.22, 309.6, 129.08]
person: 1.00 [252.79, 46.48, 636.74, 375.81]
person: 1.00 [0.68, 0.06, 638.26, 121.15]
person: 1.00 [0.6, -0.06, 346.16, 246.56]
person: 1.00 [538.08, 52.16, 638.37, 173.23]
person: 1.00 [491.73, 12.13, 638.8, 456.34]
person: 1.00 [425.46, 25.33, 640.99, 373.4]
person: 1.00 [0.28, 131.58, 104.88, 471.05]
person: 1.00 [-28.17, -6.42, 603.09, 363.32]
person: 1.00 [334.83, 92.94, 366.77, 247.36]
person: 1.00 [1.08, 59.42, 316.2, 472.36]
person: 1.00 [314.86, 296.47, 636.58, 475.68]
person: 1.00 [-15.84, -83.0, 592.57, 396.41]
person: 1.00 [336.01, 76.63, 396.59, 319.83]
person: 1.00 [382.79, 72.34, 573.73, 280.94]
person: 1.00 [128.7, 100.72, 482.46, 342.77]
person: 1.00 [-0.86, 50.07, 608.39, 301.51]
person: 1.00 [364.86, 73.13, 388.2, 106.67]
person: 1.00 [1.21, 32.98, 179.92, 253.96]
person: 1.00 [180.18, 54.78, 318.81, 239.11]
person: 1.00 [9.61, 38.79, 639.13, 472.02]
person: 1.00 [1.54, 51.77, 316.49, 325.46]
person: 1.00 [340.6, 76.51, 370.03, 98.49]
person: 1.00 [17.32, 215.85, 218.81, 472.48]
person: 1.00 [1.8, 260.97, 74.21, 472.16]
person: 1.00 [162.18, 101.62, 638.44, 474.12]
person: 1.00 [0.21, -0.03, 640.19, 121.75]
person: 1.00 [8.45, 243.09, 194.34, 468.54]
person: 1.00 [0.37, 30.73, 83.28, 471.32]
person: 1.00 [336.06, 77.69, 440.21, 353.98]
person: 1.00 [343.71, 98.27, 585.57, 352.21]
person: 1.00 [569.03, 54.91, 638.27, 87.99]
person: 1.00 [349.85, 199.06, 580.5, 371.36]
person: 1.00 [-5.68, 0.19, 615.74, 478.37]
person: 1.00 [19.14, 66.82, 596.88, 306.63]
person: 1.00 [-0.11, 57.04, 49.94, 226.28]
person: 1.00 [-7.56, -21.22, 319.02, 381.06]
person: 1.00 [-1.29, 53.2, 309.89, 473.24]
person: 1.00 [12.82, 15.03, 248.0, 322.41]
person: 1.00 [516.15, 119.23, 639.08, 474.0]
person: 1.00 [18.63, 199.56, 221.1, 473.27]
person: 1.00 [497.05, 117.41, 639.74, 473.1]
person: 1.00 [9.79, 118.04, 297.19, 454.02]
person: 1.00 [3.34, 358.19, 641.11, 477.52]
person: 1.00 [172.61, 57.34, 320.07, 239.83]
person: 1.00 [1.02, 54.99, 183.33, 473.55]
person: 1.00 [55.08, 396.24, 425.23, 477.13]
person: 1.00 [41.17, 76.11, 106.77, 116.85]
person: 1.00 [6.81, 44.78, 39.15, 108.71]
person: 1.00 [175.53, 55.39, 319.92, 238.32]
person: 1.00 [143.4, 25.21, 636.62, 372.52]
person: 1.00 [233.7, 53.43, 382.07, 192.45]
person: 1.00 [348.71, 189.82, 580.6, 371.47]
person: 1.00 [220.17, 54.97, 315.42, 141.13]
person: 1.00 [0.11, 2.01, 213.73, 472.97]
person: 1.00 [569.18, 105.69, 632.75, 223.87]
person: 1.00 [347.64, 129.3, 581.54, 372.06]
person: 1.00 [36.19, 57.23, 315.95, 240.78]
person: 1.00 [333.96, 77.02, 369.67, 186.11]
person: 1.00 [8.43, 161.46, 631.11, 443.6]
person: 1.00 [349.32, 197.01, 585.32, 310.25]
person: 1.00 [179.19, 9.84, 637.71, 314.29]
person: 1.00 [567.7, 54.52, 638.05, 87.81]
person: 1.00 [343.33, 76.47, 368.09, 116.57]
person: 1.00 [334.01, 25.98, 640.51, 210.25]
person: 1.00 [-0.24, -0.37, 476.16, 58.04]
person: 1.00 [365.76, 72.45, 388.16, 97.67]
person: 1.00 [5.58, 48.1, 556.11, 321.49]
person: 1.00 [479.51, 0.24, 639.99, 138.34]
person: 1.00 [112.97, 54.48, 320.09, 319.25]
person: 1.00 [96.5, 170.52, 591.23, 385.25]
person: 1.00 [18.35, 208.82, 634.48, 435.54]
person: 1.00 [203.47, 54.36, 315.21, 181.25]
person: 1.00 [6.79, 38.45, 95.96, 202.38]
person: 1.00 [35.03, 83.94, 585.53, 336.66]
person: 1.00 [-1.06, 46.68, 322.56, 431.87]
person: 1.00 [333.98, 76.84, 369.62, 186.06]
person: 1.00 [340.02, 76.48, 582.81, 371.45]
person: 1.00 [115.9, 44.38, 574.69, 256.77]
person: 1.00 [347.19, 182.82, 584.57, 326.97]
person: 1.00 [292.2, 99.52, 312.06, 109.58]
person: 1.00 [130.86, 25.02, 634.26, 374.85]
person: 1.00 [20.14, -56.34, 569.14, 422.56]
person: 1.00 [493.6, 23.8, 639.67, 203.12]
person: 1.00 [340.95, 90.61, 366.48, 126.22]
person: 1.00 [338.55, 76.9, 369.83, 129.09]
person: 1.00 [0.4, -1.09, 397.33, 47.79]
person: 1.00 [-5.2, 183.06, 631.77, 380.65]
person: 1.00 [2.09, 53.29, 318.05, 266.63]
person: 1.00 [-17.94, -90.57, 591.21, 388.28]
person: 1.00 [494.47, 0.84, 640.16, 158.92]
person: 1.00 [39.41, 20.58, 622.99, 320.53]
person: 1.00 [349.8, 216.39, 586.93, 371.11]
person: 1.00 [3.41, 72.11, 168.76, 463.4]
person: 1.00 [333.96, 127.41, 354.65, 186.02]
person: 1.00 [21.7, -50.29, 546.78, 413.27]
person: 1.00 [349.67, 201.48, 579.65, 371.36]
person: 1.00 [44.24, 73.55, 177.53, 102.62]
person: 1.00 [260.45, 100.7, 309.76, 141.39]
person: 1.00 [334.24, 127.85, 354.47, 185.53]
person: 1.00 [11.41, 167.25, 587.53, 383.86]
person: 1.00 [338.72, 76.53, 369.79, 121.35]
person: 1.00 [334.4, 154.26, 351.33, 186.84]
person: 1.00 [0.52, 0.42, 638.42, 86.97]
person: 1.00 [336.65, 74.82, 380.12, 162.23]
person: 1.00 [248.96, 27.01, 637.61, 474.17]
person: 1.00 [313.42, 59.9, 500.07, 257.06]
person: 1.00 [5.76, 6.61, 291.94, 327.65]
person: 1.00 [113.73, 21.36, 633.36, 379.54]
person: 1.00 [16.32, 82.46, 68.45, 241.11]
person: 1.00 [516.34, -4.28, 593.78, 48.09]
person: 1.00 [1.01, 0.37, 207.69, 239.27]
person: 1.00 [-0.22, 52.25, 70.18, 130.13]
person: 1.00 [26.83, 323.37, 73.32, 471.25]
person: 1.00 [352.95, 25.03, 640.83, 201.57]
person: 1.00 [-0.55, -1.35, 305.24, 42.25]
person: 1.00 [358.3, 24.66, 640.36, 209.21]
person: 1.00 [4.82, 60.29, 387.41, 474.41]
person: 1.00 [442.45, 218.22, 493.46, 290.22]
```
![false](https://github.com/user-attachments/assets/c19c6be1-df44-4033-92ca-5cf6585bdc0c)



### Solved
Fixes a critical bug in the [`post_process_object_detection`](https://github.com/huggingface/transformers/blob/984bc11b0882ff1e5b34ba717ea357e069ceced9/src/transformers/models/rt_detr/image_processing_rt_detr.py#L1084)
`scores = torch.nn.functional.softmax(out_logits)[:, :, :-1]` 
-> `scores = torch.nn.functional.softmax(out_logits,dim-1)`

Comments:
Hi @dwchoo thank you for reporting the issue and submitting a PR, I will check this out!

cc @SangbumChoi 

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