fix incorrect yolov7 IS test

Author: leeclemnet

inference_models/tests/integration_tests/models/test_yolov7_instance_segmentation_predictions_onnx.py

@@ -33,7 +33,7 @@ def test_seg_onnx_package_with_static_batch_size_and_letterbox_numpy(
     assert np.allclose(
         predictions[0].xyxy[0].cpu().numpy(), [59, 162, 192, 387], atol=1
     )
-    assert np.allclose(predictions[0].class_id[0].cpu().numpy(), [0], atol=1)
+    assert np.allclose(predictions[0].class_id[0].cpu().numpy(), [21], atol=1)
     assert np.allclose(predictions[0].confidence[0].cpu().numpy(), [0.7349], atol=0.005)
     assert 16600 <= predictions[0].mask[0].cpu().numpy().sum() <= 16900
 
@@ -68,13 +68,13 @@ def test_seg_onnx_package_with_static_batch_size_and_letterbox_numpy_list(
     assert np.allclose(
         predictions[0].xyxy[0].cpu().numpy(), [59, 162, 192, 387], atol=1
     )
-    assert np.allclose(predictions[0].class_id[0].cpu().numpy(), [0], atol=1)
+    assert np.allclose(predictions[0].class_id[0].cpu().numpy(), [21], atol=1)
     assert np.allclose(predictions[0].confidence[0].cpu().numpy(), [0.7349], atol=0.005)
     assert 16600 <= predictions[0].mask[0].cpu().numpy().sum() <= 16900
     assert np.allclose(
         predictions[1].xyxy[0].cpu().numpy(), [59, 162, 192, 387], atol=1
     )
-    assert np.allclose(predictions[1].class_id[0].cpu().numpy(), [0], atol=1)
+    assert np.allclose(predictions[1].class_id[0].cpu().numpy(), [21], atol=1)
     assert np.allclose(predictions[1].confidence[0].cpu().numpy(), [0.7349], atol=0.005)
     assert 16600 <= predictions[1].mask[0].cpu().numpy().sum() <= 16900
 
@@ -108,7 +108,7 @@ def test_seg_onnx_package_with_static_batch_size_and_letterbox_torch(
     assert np.allclose(
         predictions[0].xyxy[0].cpu().numpy(), [59, 162, 192, 387], atol=1
     )
-    assert np.allclose(predictions[0].class_id[0].cpu().numpy(), [0], atol=1)
+    assert np.allclose(predictions[0].class_id[0].cpu().numpy(), [21], atol=1)
     assert np.allclose(predictions[0].confidence[0].cpu().numpy(), [0.7349], atol=0.005)
     assert 16600 <= predictions[0].mask[0].cpu().numpy().sum() <= 16900
 
@@ -142,13 +142,13 @@ def test_seg_onnx_package_with_static_batch_size_and_letterbox_torch_list(
     assert np.allclose(
         predictions[0].xyxy[0].cpu().numpy(), [59, 162, 192, 387], atol=1
     )
-    assert np.allclose(predictions[0].class_id[0].cpu().numpy(), [0], atol=1)
+    assert np.allclose(predictions[0].class_id[0].cpu().numpy(), [21], atol=1)
     assert np.allclose(predictions[0].confidence[0].cpu().numpy(), [0.7349], atol=0.005)
     assert 16600 <= predictions[0].mask[0].cpu().numpy().sum() <= 16900
     assert np.allclose(
         predictions[1].xyxy[0].cpu().numpy(), [59, 162, 192, 387], atol=1
     )
-    assert np.allclose(predictions[1].class_id[0].cpu().numpy(), [0], atol=1)
+    assert np.allclose(predictions[1].class_id[0].cpu().numpy(), [21], atol=1)
     assert np.allclose(predictions[1].confidence[0].cpu().numpy(), [0.7349], atol=0.005)
     assert 16600 <= predictions[1].mask[0].cpu().numpy().sum() <= 16900
 
@@ -182,12 +182,12 @@ def test_seg_onnx_package_with_static_batch_size_and_letterbox_torch_tensor(
     assert np.allclose(
         predictions[0].xyxy[0].cpu().numpy(), [59, 162, 192, 387], atol=1
     )
-    assert np.allclose(predictions[0].class_id[0].cpu().numpy(), [0], atol=1)
+    assert np.allclose(predictions[0].class_id[0].cpu().numpy(), [21], atol=1)
     assert np.allclose(predictions[0].confidence[0].cpu().numpy(), [0.7349], atol=0.005)
     assert 16600 <= predictions[0].mask[0].cpu().numpy().sum() <= 16900
     assert np.allclose(
         predictions[1].xyxy[0].cpu().numpy(), [59, 162, 192, 387], atol=1
     )
-    assert np.allclose(predictions[1].class_id[0].cpu().numpy(), [0], atol=1)
+    assert np.allclose(predictions[1].class_id[0].cpu().numpy(), [21], atol=1)
     assert np.allclose(predictions[1].confidence[0].cpu().numpy(), [0.7349], atol=0.005)
     assert 16600 <= predictions[1].mask[0].cpu().numpy().sum() <= 16900