Simplify Results() class (#4579)

tests/test_python.py

@@ -217,7 +217,7 @@ def test_all_model_yamls():
     for m in (ROOT / 'cfg' / 'models').rglob('*.yaml'):
         if 'rtdetr' in m.name:
             if TORCH_1_9:  # torch<=1.8 issue - TypeError: __init__() got an unexpected keyword argument 'batch_first'
-                RTDETR(m.name)(SOURCE, imgsz=640)
+                RTDETR(m.name)(SOURCE, imgsz=640)  # must be 640
         else:
             YOLO(m.name)
 
@@ -225,8 +225,8 @@ def test_all_model_yamls():
 def test_workflow():
     model = YOLO(MODEL)
     model.train(data='coco8.yaml', epochs=1, imgsz=32)
-    model.val()
-    model.predict(SOURCE)
+    model.val(imgsz=32)
+    model.predict(SOURCE, imgsz=32)
     model.export(format='onnx')  # export a model to ONNX format
 
 
@@ -243,7 +243,7 @@ def test_predict_callback_and_setup():
 
     dataset = load_inference_source(source=SOURCE)
     bs = dataset.bs  # noqa access predictor properties
-    results = model.predict(dataset, stream=True)  # source already setup
+    results = model.predict(dataset, stream=True, imgsz=160)  # source already setup
     for r, im0, bs in results:
         print('test_callback', im0.shape)
         print('test_callback', bs)
@@ -254,7 +254,7 @@ def test_predict_callback_and_setup():
 def test_results():
     for m in 'yolov8n-pose.pt', 'yolov8n-seg.pt', 'yolov8n.pt', 'yolov8n-cls.pt':
         model = YOLO(m)
-        results = model([SOURCE, SOURCE])
+        results = model([SOURCE, SOURCE], imgsz=160)
         for r in results:
             r = r.cpu().numpy()
             r = r.to(device='cpu', dtype=torch.float32)
@@ -263,10 +263,7 @@ def test_results():
             r.tojson(normalize=True)
             r.plot(pil=True)
             r.plot(conf=True, boxes=True)
-            print(r)
-            print(r.path)
-            for k in r.keys:
-                print(getattr(r, k))
+            print(r, len(r), r.path)
 
 
 @pytest.mark.skipif(not ONLINE, reason='environment is offline')