| 2026-06-03 16:31:49.243860: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations. |
| To enable the following instructions: AVX2 FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags. |
| 2026-06-03 16:31:52.095285: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT |
| 2026-06-03 16:31:59.966324: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1639] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 46732 MB memory: -> device: 0, name: NVIDIA RTX A6000, pci bus id: 0000:41:00.0, compute capability: 8.6 |
| WARNING:absl:Skipping variable loading for optimizer 'RMSprop', because it has 1 variables whereas the saved optimizer has 301 variables. |
| 2026-06-03 16:32:05.682868: I tensorflow/compiler/xla/stream_executor/cuda/cuda_dnn.cc:432] Loaded cuDNN version 8907 |
| 2026-06-03 16:32:05.816842: I tensorflow/tsl/platform/default/subprocess.cc:304] Start cannot spawn child process: No such file or directory |
| 2026-06-03 16:32:06.284320: I tensorflow/compiler/xla/stream_executor/cuda/cuda_blas.cc:606] TensorFloat-32 will be used for the matrix multiplication. This will only be logged once. |
| Building model… |
| Weights loaded. |
|
|
| Loading 92 test images… |
| Predicting… |
|
1/12 [=>............................] - ETA: 21s
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12/12 [==============================] - ETA: 0s
12/12 [==============================] - 3s 70ms/step |
| |
| ============================================================ |
| ROCKGLACIERNET — EVALUATION SUMMARY (baseline 128x128) |
| ============================================================ |
| |
| Test images : 92 |
| Best threshold by IoU : 0.65 |
| |
| GLOBAL (pixel-pooled) metrics @ best threshold: |
| precision : 0.6935 |
| recall : 0.8028 |
| f1 : 0.7442 |
| iou : 0.5926 |
| dice : 0.7442 |
| |
| PER-IMAGE IoU (@ t=0.5): |
| mean : 0.6622 |
| median : 0.6957 |
| |
| Threshold sweep: |
| thresh precision recall f1 iou dice |
| ------------------------------------------------------------ |
| 0.3 0.6169 0.8922 0.7294 0.5741 0.7294 |
| 0.35 0.6276 0.8812 0.7331 0.5786 0.7331 |
| 0.4 0.6382 0.8699 0.7363 0.5826 0.7363 |
| 0.45 0.6483 0.8583 0.7387 0.5856 0.7387 |
| 0.5 0.6582 0.8463 0.7405 0.5879 0.7405 |
| 0.55 0.6689 0.8332 0.7421 0.5899 0.7421 |
| 0.6 0.6807 0.8193 0.7436 0.5919 0.7436 |
| 0.65 0.6935 0.8028 0.7442 0.5926 0.7442 <- best IoU |
| 0.7 0.7081 0.7822 0.7433 0.5915 0.7433 |
| |
| 10 WORST images by IoU (@ t=0.5): |
| image_id orig_H orig_W glacier_frac_gt iou precision recall |
| 0242 130 120 0.1247 0.2662 0.2758 0.8841 |
| 0286 289 177 0.3099 0.3416 0.3696 0.8186 |
| 0450 80 82 0.0709 0.3615 0.3849 0.8559 |
| 0288 250 115 0.2682 0.3783 0.5689 0.5304 |
| 0301 125 84 0.1251 0.3966 0.4103 0.9224 |
| 0491 141 74 0.1455 0.4199 0.4927 0.7395 |
| 0615 91 60 0.0974 0.4655 0.5520 0.7481 |
| 0234 98 110 0.2587 0.4680 0.8010 0.5296 |
| 0032 55 60 0.0436 0.4833 0.5472 0.8056 |
| 0268 146 135 0.2199 0.4892 0.6085 0.7138 |
| |
| Output dir: outputs/predictions/baseline_model_output |
| Files: per_image_metrics.csv, evaluation_metrics.csv, confusion_matrix.csv |
| Saved 20 comparison PNGs (10 worst + 10 best). |
| |
| Evaluation complete. |
| |
