2024-03-17 09:38:30,661 [INFO] datautils - Initialized dataset: AlekseyKorshuk/product-photography-all 2024-03-17 13:03:31,098 [INFO] datautils - Initialized dataset: AlekseyKorshuk/product-photography-all 2024-03-17 13:04:18,258 [INFO] datautils - Initialized dataset: AlekseyKorshuk/product-photography-all 2024-03-17 13:05:30,826 [INFO] datautils - Initialized dataset: AlekseyKorshuk/product-photography-all 2024-03-17 13:06:16,536 [INFO] datautils - Initialized dataset: AlekseyKorshuk/product-photography-all 2024-03-17 13:08:54,239 [INFO] datautils - Initialized dataset: AlekseyKorshuk/product-photography-all 2024-03-17 13:08:54,345 [INFO] datautils - {'id': '1d74b94308b6ed746c4c1e848d9646bbf39d9ee60180773b47a1d50e2e70792f', 'image': , 'image_mask': , 'text': 'colorful tacos with fresh ingredients on a blue patterned ceramic plate, front and center on a wooden counter, amidst a lively market with hanging papel picado and ambient lighting, an overhead angled view capturing the festive vibe and the bustling crowd in the background'} 2024-03-17 13:10:35,437 [INFO] datautils - Initialized dataset: AlekseyKorshuk/product-photography-all 2024-03-17 13:11:43,102 [INFO] datautils - Initialized dataset: AlekseyKorshuk/product-photography-all 2024-03-17 13:11:43,111 [INFO] datautils - {'id': Value(dtype='string', id=None), 'image': Image(decode=True, id=None), 'image_mask': Image(decode=True, id=None), 'text': Value(dtype='string', id=None)} 2024-03-17 13:19:37,507 [INFO] datautils - Initialized dataset: AlekseyKorshuk/product-photography-all 2024-03-17 13:19:56,651 [INFO] datautils - Initialized dataset: AlekseyKorshuk/product-photography-all 2024-03-17 13:19:56,655 [INFO] datautils - {'id': Value(dtype='string', id=None), 'image': Image(decode=True, id=None), 'image_mask': Image(decode=True, id=None), 'text': Value(dtype='string', id=None)} 2024-03-17 13:20:12,325 [INFO] datautils - Initialized dataset: AlekseyKorshuk/product-photography-all 2024-03-17 13:20:12,332 [INFO] datautils - {'id': Value(dtype='string', id=None), 'image': Image(decode=True, id=None), 'image_mask': Image(decode=True, id=None), 'text': Value(dtype='string', id=None)} 2024-03-17 13:20:12,341 [INFO] datautils - {'id': Value(dtype='string', id=None), 'image': Image(decode=True, id=None), 'image_mask': Image(decode=True, id=None), 'text': Value(dtype='string', id=None)} 2024-03-17 13:20:36,315 [INFO] datautils - Initialized dataset: AlekseyKorshuk/product-photography-all 2024-03-17 13:20:36,322 [INFO] datautils - {'id': Value(dtype='string', id=None), 'image': Image(decode=True, id=None), 'image_mask': Image(decode=True, id=None), 'text': Value(dtype='string', id=None)} 2024-03-17 13:20:36,331 [INFO] datautils - {'image': Image(decode=True, id=None), 'image_mask': Image(decode=True, id=None), 'text': Value(dtype='string', id=None)} 2024-03-17 13:22:52,574 [INFO] datautils - Initialized dataset: AlekseyKorshuk/product-photography-all 2024-03-17 13:23:56,762 [INFO] datautils - Initialized dataset: AlekseyKorshuk/product-photography-all 2024-03-17 13:24:19,651 [INFO] datautils - Initialized dataset: AlekseyKorshuk/product-photography-all 2024-03-17 13:24:47,952 [INFO] datautils - Initialized dataset: AlekseyKorshuk/product-photography-all 2024-03-17 13:25:48,675 [INFO] datautils - Initialized dataset: AlekseyKorshuk/product-photography-all 2024-03-17 13:26:15,674 [INFO] datautils - Initialized dataset: AlekseyKorshuk/product-photography-all 2024-03-17 13:26:51,526 [INFO] datautils - Initialized dataset: AlekseyKorshuk/product-photography-all 2024-03-17 13:26:51,586 [INFO] datautils - {'image': Image(decode=False, id=None), 'image_mask': Image(decode=False, id=None), 'text': Value(dtype='string', id=None)} 2024-03-17 13:31:18,337 [INFO] datautils - Initialized dataset: AlekseyKorshuk/product-photography-all 2024-03-17 13:38:51,491 [INFO] datautils - Initialized dataset: AlekseyKorshuk/product-photography-all 2024-03-17 13:44:33,279 [INFO] datautils - Initialized dataset: AlekseyKorshuk/product-photography-all 2024-03-17 13:49:05,014 [INFO] datautils - Initialized dataset: AlekseyKorshuk/product-photography-all 2024-03-17 13:51:10,211 [INFO] datautils - Initialized dataset: AlekseyKorshuk/product-photography-all 2024-03-17 13:51:10,259 [INFO] datautils - {'image': Image(decode=True, id=None), 'image_mask': Image(decode=True, id=None), 'text': Value(dtype='string', id=None)} 2024-03-17 13:54:14,988 [INFO] datautils - Initialized dataset: AlekseyKorshuk/product-photography-all 2024-03-17 13:54:15,025 [INFO] datautils - {'image': Image(decode=True, id=None), 'image_mask': Image(decode=True, id=None), 'text': Value(dtype='string', id=None)} 2024-03-17 13:55:43,694 [INFO] datautils - Initialized dataset: AlekseyKorshuk/product-photography-all 2024-03-17 13:55:43,756 [INFO] datautils - {'image': Image(decode=True, id=None), 'image_mask': Image(decode=True, id=None), 'text': Value(dtype='string', id=None)} 2024-03-17 13:57:55,463 [INFO] datautils - Initialized dataset: AlekseyKorshuk/product-photography-all 2024-03-17 13:57:55,520 [INFO] datautils - {'image': Image(decode=False, id=None), 'image_mask': Image(decode=False, id=None), 'text': Value(dtype='string', id=None)} 2024-03-17 13:58:51,294 [INFO] datautils - Initialized dataset: AlekseyKorshuk/product-photography-all 2024-03-17 13:58:51,345 [INFO] datautils - {'image': Image(decode=False, id=None), 'image_mask': Image(decode=False, id=None), 'text': Value(dtype='string', id=None)} 2024-03-17 14:01:42,885 [INFO] datautils - Initialized dataset: AlekseyKorshuk/product-photography-all 2024-03-17 14:01:42,920 [INFO] datautils - {'image': Image(decode=False, id=None), 'image_mask': Image(decode=False, id=None), 'text': Value(dtype='string', id=None)} 2024-03-17 14:03:00,409 [INFO] datautils - Initialized dataset: AlekseyKorshuk/product-photography-all 2024-03-17 14:03:00,468 [INFO] datautils - {'image': Image(decode=True, id=None), 'image_mask': Image(decode=True, id=None), 'text': Value(dtype='string', id=None)} 2024-03-17 14:09:05,056 [INFO] datautils - Initialized dataset: AlekseyKorshuk/product-photography-all 2024-03-17 14:09:05,092 [INFO] datautils - {'image': Image(decode=False, id=None), 'image_mask': Image(decode=True, id=None), 'text': Value(dtype='string', id=None)} 2024-03-17 14:09:51,895 [INFO] datautils - Initialized dataset: AlekseyKorshuk/product-photography-all 2024-03-17 14:09:51,943 [INFO] datautils - {'image': Image(decode=False, id=None), 'image_mask': Image(decode=True, id=None), 'text': Value(dtype='string', id=None)} 2024-03-17 14:18:43,105 [INFO] datautils - Initialized dataset: AlekseyKorshuk/product-photography-all 2024-03-17 14:18:43,160 [INFO] datautils - {'image': Image(decode=False, id=None), 'image_mask': Image(decode=True, id=None), 'text': Value(dtype='string', id=None)} 2024-03-17 14:27:24,939 [INFO] datautils - Initialized dataset: AlekseyKorshuk/product-photography-all 2024-03-17 14:27:25,026 [INFO] datautils - {'image': Image(decode=False, id=None), 'image_mask': Image(decode=True, id=None), 'text': Value(dtype='string', id=None)} 2024-03-17 14:43:27,682 [INFO] datautils - Initialized dataset: AlekseyKorshuk/product-photography-all 2024-03-17 14:43:27,808 [INFO] datautils - {'image': Image(decode=False, id=None), 'image_mask': Image(decode=True, id=None), 'text': Value(dtype='string', id=None)} 2024-03-17 14:45:48,573 [INFO] datautils - Initialized dataset: AlekseyKorshuk/product-photography-all 2024-03-17 14:45:48,620 [INFO] datautils - {'image': Image(decode=False, id=None), 'image_mask': Image(decode=True, id=None), 'text': Value(dtype='string', id=None)} 2024-03-17 14:53:40,844 [INFO] datautils - Initialized dataset: AlekseyKorshuk/product-photography-all 2024-03-17 14:53:40,891 [INFO] datautils - {'image': Image(decode=False, id=None), 'image_mask': Image(decode=True, id=None), 'text': Value(dtype='string', id=None)} 2024-03-17 14:56:56,233 [INFO] datautils - Initialized dataset: AlekseyKorshuk/product-photography-all 2024-03-17 14:56:56,324 [INFO] datautils - {'image': Image(decode=False, id=None), 'image_mask': Image(decode=True, id=None), 'text': Value(dtype='string', id=None)} 2024-03-17 15:04:17,000 [INFO] datautils - Initialized dataset: AlekseyKorshuk/product-photography-all 2024-03-17 15:04:17,049 [INFO] datautils - {'image': Image(decode=False, id=None), 'image_mask': Image(decode=True, id=None), 'text': Value(dtype='string', id=None)} 2024-03-17 15:13:35,862 [INFO] datautils - Initialized dataset: AlekseyKorshuk/product-photography-all 2024-03-17 15:13:35,871 [INFO] datautils - {'image': Image(decode=True, id=None), 'image_mask': Image(decode=True, id=None), 'text': Value(dtype='string', id=None)} 2024-03-17 15:24:02,618 [INFO] datautils - Initialized dataset: AlekseyKorshuk/product-photography-all 2024-03-17 15:24:02,632 [INFO] datautils - {'image': Image(decode=True, id=None), 'image_mask': Image(decode=True, id=None), 'text': Value(dtype='string', id=None)} 2024-03-18 08:25:52,098 [INFO] mask_generator - Generated 5 masks 2024-03-18 08:25:52,107 [INFO] mask_generator - [ultralytics.engine.results.Results object with attributes: boxes: ultralytics.engine.results.Boxes object keypoints: None masks: ultralytics.engine.results.Masks object names: {0: '0', 1: '1', 2: '2', 3: '3', 4: '4', 5: '5', 6: '6', 7: '7', 8: '8', 9: '9', 10: '10', 11: '11', 12: '12', 13: '13', 14: '14', 15: '15', 16: '16', 17: '17', 18: '18', 19: '19', 20: '20', 21: '21', 22: '22', 23: '23', 24: '24', 25: '25', 26: '26', 27: '27', 28: '28', 29: '29'} obb: None orig_img: array([[[254, 254, 254], [254, 254, 254], [254, 254, 254], ..., [254, 254, 254], [254, 254, 254], [254, 254, 254]], [[254, 254, 254], [254, 254, 254], [254, 254, 254], ..., [254, 254, 254], [254, 254, 254], [254, 254, 254]], [[254, 254, 254], [254, 254, 254], [254, 254, 254], ..., [254, 254, 254], [254, 254, 254], [254, 254, 254]], ..., [[254, 254, 254], [254, 254, 254], [254, 254, 254], ..., [254, 254, 254], [254, 254, 254], [254, 254, 254]], [[254, 254, 254], [254, 254, 254], [254, 254, 254], ..., [254, 254, 254], [254, 254, 254], [254, 254, 254]], [[254, 254, 254], [254, 254, 254], [254, 254, 254], ..., [254, 254, 254], [254, 254, 254], [254, 254, 254]]], dtype=uint8) orig_shape: (523, 679) path: 'image0.jpg' probs: None save_dir: 'runs/segment/predict' speed: {'preprocess': 31.74138069152832, 'inference': 3650.0487327575684, 'postprocess': 1.4531612396240234}] 2024-03-18 08:43:24,186 [INFO] mask_generator - Generated 5 masks 2024-03-18 08:44:04,507 [INFO] mask_generator - Generated 5 masks 2024-03-18 08:51:11,413 [INFO] mask_generator - Generated 5 masks 2024-03-18 08:51:11,419 [INFO] mask_generator - [ultralytics.engine.results.Results object with attributes: boxes: ultralytics.engine.results.Boxes object keypoints: None masks: ultralytics.engine.results.Masks object names: {0: 'person', 1: 'bicycle', 2: 'car', 3: 'motorcycle', 4: 'airplane', 5: 'bus', 6: 'train', 7: 'truck', 8: 'boat', 9: 'traffic light', 10: 'fire hydrant', 11: 'stop sign', 12: 'parking meter', 13: 'bench', 14: 'bird', 15: 'cat', 16: 'dog', 17: 'horse', 18: 'sheep', 19: 'cow', 20: 'elephant', 21: 'bear', 22: 'zebra', 23: 'giraffe', 24: 'backpack', 25: 'umbrella', 26: 'handbag', 27: 'tie', 28: 'suitcase', 29: 'frisbee', 30: 'skis', 31: 'snowboard', 32: 'sports ball', 33: 'kite', 34: 'baseball bat', 35: 'baseball glove', 36: 'skateboard', 37: 'surfboard', 38: 'tennis racket', 39: 'bottle', 40: 'wine glass', 41: 'cup', 42: 'fork', 43: 'knife', 44: 'spoon', 45: 'bowl', 46: 'banana', 47: 'apple', 48: 'sandwich', 49: 'orange', 50: 'broccoli', 51: 'carrot', 52: 'hot dog', 53: 'pizza', 54: 'donut', 55: 'cake', 56: 'chair', 57: 'couch', 58: 'potted plant', 59: 'bed', 60: 'dining table', 61: 'toilet', 62: 'tv', 63: 'laptop', 64: 'mouse', 65: 'remote', 66: 'keyboard', 67: 'cell phone', 68: 'microwave', 69: 'oven', 70: 'toaster', 71: 'sink', 72: 'refrigerator', 73: 'book', 74: 'clock', 75: 'vase', 76: 'scissors', 77: 'teddy bear', 78: 'hair drier', 79: 'toothbrush'} obb: None orig_img: array([[[254, 254, 254], [254, 254, 254], [254, 254, 254], ..., [254, 254, 254], [254, 254, 254], [254, 254, 254]], [[254, 254, 254], [254, 254, 254], [254, 254, 254], ..., [254, 254, 254], [254, 254, 254], [254, 254, 254]], [[254, 254, 254], [254, 254, 254], [254, 254, 254], ..., [254, 254, 254], [254, 254, 254], [254, 254, 254]], ..., [[254, 254, 254], [254, 254, 254], [254, 254, 254], ..., [254, 254, 254], [254, 254, 254], [254, 254, 254]], [[254, 254, 254], [254, 254, 254], [254, 254, 254], ..., [254, 254, 254], [254, 254, 254], [254, 254, 254]], [[254, 254, 254], [254, 254, 254], [254, 254, 254], ..., [254, 254, 254], [254, 254, 254], [254, 254, 254]]], dtype=uint8) orig_shape: (523, 679) path: 'image0.jpg' probs: None save_dir: 'runs/segment/predict' speed: {'preprocess': 188.57908248901367, 'inference': 143.46075057983398, 'postprocess': 599.8485088348389}] 2024-03-18 08:54:25,891 [INFO] mask_generator - Generated 5 masks 2024-03-18 08:54:25,896 [INFO] mask_generator - [[ultralytics.engine.results.Results object with attributes: boxes: ultralytics.engine.results.Boxes object keypoints: None masks: ultralytics.engine.results.Masks object names: {0: 'person', 1: 'bicycle', 2: 'car', 3: 'motorcycle', 4: 'airplane', 5: 'bus', 6: 'train', 7: 'truck', 8: 'boat', 9: 'traffic light', 10: 'fire hydrant', 11: 'stop sign', 12: 'parking meter', 13: 'bench', 14: 'bird', 15: 'cat', 16: 'dog', 17: 'horse', 18: 'sheep', 19: 'cow', 20: 'elephant', 21: 'bear', 22: 'zebra', 23: 'giraffe', 24: 'backpack', 25: 'umbrella', 26: 'handbag', 27: 'tie', 28: 'suitcase', 29: 'frisbee', 30: 'skis', 31: 'snowboard', 32: 'sports ball', 33: 'kite', 34: 'baseball bat', 35: 'baseball glove', 36: 'skateboard', 37: 'surfboard', 38: 'tennis racket', 39: 'bottle', 40: 'wine glass', 41: 'cup', 42: 'fork', 43: 'knife', 44: 'spoon', 45: 'bowl', 46: 'banana', 47: 'apple', 48: 'sandwich', 49: 'orange', 50: 'broccoli', 51: 'carrot', 52: 'hot dog', 53: 'pizza', 54: 'donut', 55: 'cake', 56: 'chair', 57: 'couch', 58: 'potted plant', 59: 'bed', 60: 'dining table', 61: 'toilet', 62: 'tv', 63: 'laptop', 64: 'mouse', 65: 'remote', 66: 'keyboard', 67: 'cell phone', 68: 'microwave', 69: 'oven', 70: 'toaster', 71: 'sink', 72: 'refrigerator', 73: 'book', 74: 'clock', 75: 'vase', 76: 'scissors', 77: 'teddy bear', 78: 'hair drier', 79: 'toothbrush'} obb: None orig_img: array([[[254, 254, 254], [254, 254, 254], [254, 254, 254], ..., [254, 254, 254], [254, 254, 254], [254, 254, 254]], [[254, 254, 254], [254, 254, 254], [254, 254, 254], ..., [254, 254, 254], [254, 254, 254], [254, 254, 254]], [[254, 254, 254], [254, 254, 254], [254, 254, 254], ..., [254, 254, 254], [254, 254, 254], [254, 254, 254]], ..., [[254, 254, 254], [254, 254, 254], [254, 254, 254], ..., [254, 254, 254], [254, 254, 254], [254, 254, 254]], [[254, 254, 254], [254, 254, 254], [254, 254, 254], ..., [254, 254, 254], [254, 254, 254], [254, 254, 254]], [[254, 254, 254], [254, 254, 254], [254, 254, 254], ..., [254, 254, 254], [254, 254, 254], [254, 254, 254]]], dtype=uint8) orig_shape: (523, 679) path: 'image0.jpg' probs: None save_dir: 'runs/segment/predict' speed: {'preprocess': 4.889011383056641, 'inference': 92.71430969238281, 'postprocess': 522.0129489898682}], [ultralytics.engine.results.Results object with attributes: boxes: ultralytics.engine.results.Boxes object keypoints: None masks: ultralytics.engine.results.Masks object names: {0: 'person', 1: 'bicycle', 2: 'car', 3: 'motorcycle', 4: 'airplane', 5: 'bus', 6: 'train', 7: 'truck', 8: 'boat', 9: 'traffic light', 10: 'fire hydrant', 11: 'stop sign', 12: 'parking meter', 13: 'bench', 14: 'bird', 15: 'cat', 16: 'dog', 17: 'horse', 18: 'sheep', 19: 'cow', 20: 'elephant', 21: 'bear', 22: 'zebra', 23: 'giraffe', 24: 'backpack', 25: 'umbrella', 26: 'handbag', 27: 'tie', 28: 'suitcase', 29: 'frisbee', 30: 'skis', 31: 'snowboard', 32: 'sports ball', 33: 'kite', 34: 'baseball bat', 35: 'baseball glove', 36: 'skateboard', 37: 'surfboard', 38: 'tennis racket', 39: 'bottle', 40: 'wine glass', 41: 'cup', 42: 'fork', 43: 'knife', 44: 'spoon', 45: 'bowl', 46: 'banana', 47: 'apple', 48: 'sandwich', 49: 'orange', 50: 'broccoli', 51: 'carrot', 52: 'hot dog', 53: 'pizza', 54: 'donut', 55: 'cake', 56: 'chair', 57: 'couch', 58: 'potted plant', 59: 'bed', 60: 'dining table', 61: 'toilet', 62: 'tv', 63: 'laptop', 64: 'mouse', 65: 'remote', 66: 'keyboard', 67: 'cell phone', 68: 'microwave', 69: 'oven', 70: 'toaster', 71: 'sink', 72: 'refrigerator', 73: 'book', 74: 'clock', 75: 'vase', 76: 'scissors', 77: 'teddy bear', 78: 'hair drier', 79: 'toothbrush'} obb: None orig_img: array([[[255, 255, 255], [255, 255, 255], [255, 255, 255], ..., [255, 255, 255], [255, 255, 255], [255, 255, 255]], [[255, 255, 255], [255, 255, 255], [255, 255, 255], ..., [255, 255, 255], [255, 255, 255], [255, 255, 255]], [[255, 255, 255], [255, 255, 255], [255, 255, 255], ..., [255, 255, 255], [255, 255, 255], [255, 255, 255]], ..., [[255, 255, 255], [255, 255, 255], [255, 255, 255], ..., [255, 255, 255], [255, 255, 255], [255, 255, 255]], [[255, 255, 255], [255, 255, 255], [255, 255, 255], ..., [255, 255, 255], [255, 255, 255], [255, 255, 255]], [[255, 255, 255], [255, 255, 255], [255, 255, 255], ..., [255, 255, 255], [255, 255, 255], [255, 255, 255]]], dtype=uint8) orig_shape: (492, 679) path: 'image0.jpg' probs: None save_dir: 'runs/segment/predict' speed: {'preprocess': 3.2563209533691406, 'inference': 91.84670448303223, 'postprocess': 5.931854248046875}], [ultralytics.engine.results.Results object with attributes: boxes: ultralytics.engine.results.Boxes object keypoints: None masks: ultralytics.engine.results.Masks object names: {0: 'person', 1: 'bicycle', 2: 'car', 3: 'motorcycle', 4: 'airplane', 5: 'bus', 6: 'train', 7: 'truck', 8: 'boat', 9: 'traffic light', 10: 'fire hydrant', 11: 'stop sign', 12: 'parking meter', 13: 'bench', 14: 'bird', 15: 'cat', 16: 'dog', 17: 'horse', 18: 'sheep', 19: 'cow', 20: 'elephant', 21: 'bear', 22: 'zebra', 23: 'giraffe', 24: 'backpack', 25: 'umbrella', 26: 'handbag', 27: 'tie', 28: 'suitcase', 29: 'frisbee', 30: 'skis', 31: 'snowboard', 32: 'sports ball', 33: 'kite', 34: 'baseball bat', 35: 'baseball glove', 36: 'skateboard', 37: 'surfboard', 38: 'tennis racket', 39: 'bottle', 40: 'wine glass', 41: 'cup', 42: 'fork', 43: 'knife', 44: 'spoon', 45: 'bowl', 46: 'banana', 47: 'apple', 48: 'sandwich', 49: 'orange', 50: 'broccoli', 51: 'carrot', 52: 'hot dog', 53: 'pizza', 54: 'donut', 55: 'cake', 56: 'chair', 57: 'couch', 58: 'potted plant', 59: 'bed', 60: 'dining table', 61: 'toilet', 62: 'tv', 63: 'laptop', 64: 'mouse', 65: 'remote', 66: 'keyboard', 67: 'cell phone', 68: 'microwave', 69: 'oven', 70: 'toaster', 71: 'sink', 72: 'refrigerator', 73: 'book', 74: 'clock', 75: 'vase', 76: 'scissors', 77: 'teddy bear', 78: 'hair drier', 79: 'toothbrush'} obb: None orig_img: array([[[255, 255, 255], [255, 255, 255], [255, 255, 255], ..., [255, 255, 255], [255, 255, 255], [255, 255, 255]], [[255, 255, 255], [255, 255, 255], [255, 255, 255], ..., [255, 255, 255], [255, 255, 255], [255, 255, 255]], [[255, 255, 255], [255, 255, 255], [255, 255, 255], ..., [255, 255, 255], [255, 255, 255], [255, 255, 255]], ..., [[255, 255, 255], [255, 255, 255], [255, 255, 255], ..., [255, 255, 255], [255, 255, 255], [255, 255, 255]], [[255, 255, 255], [255, 255, 255], [255, 255, 255], ..., [255, 255, 255], [255, 255, 255], [255, 255, 255]], [[255, 255, 255], [255, 255, 255], [255, 255, 255], ..., [255, 255, 255], [255, 255, 255], [255, 255, 255]]], dtype=uint8) orig_shape: (495, 679) path: 'image0.jpg' probs: None save_dir: 'runs/segment/predict' speed: {'preprocess': 2.3126602172851562, 'inference': 6.824731826782227, 'postprocess': 1.6677379608154297}], [ultralytics.engine.results.Results object with attributes: boxes: ultralytics.engine.results.Boxes object keypoints: None masks: ultralytics.engine.results.Masks object names: {0: 'person', 1: 'bicycle', 2: 'car', 3: 'motorcycle', 4: 'airplane', 5: 'bus', 6: 'train', 7: 'truck', 8: 'boat', 9: 'traffic light', 10: 'fire hydrant', 11: 'stop sign', 12: 'parking meter', 13: 'bench', 14: 'bird', 15: 'cat', 16: 'dog', 17: 'horse', 18: 'sheep', 19: 'cow', 20: 'elephant', 21: 'bear', 22: 'zebra', 23: 'giraffe', 24: 'backpack', 25: 'umbrella', 26: 'handbag', 27: 'tie', 28: 'suitcase', 29: 'frisbee', 30: 'skis', 31: 'snowboard', 32: 'sports ball', 33: 'kite', 34: 'baseball bat', 35: 'baseball glove', 36: 'skateboard', 37: 'surfboard', 38: 'tennis racket', 39: 'bottle', 40: 'wine glass', 41: 'cup', 42: 'fork', 43: 'knife', 44: 'spoon', 45: 'bowl', 46: 'banana', 47: 'apple', 48: 'sandwich', 49: 'orange', 50: 'broccoli', 51: 'carrot', 52: 'hot dog', 53: 'pizza', 54: 'donut', 55: 'cake', 56: 'chair', 57: 'couch', 58: 'potted plant', 59: 'bed', 60: 'dining table', 61: 'toilet', 62: 'tv', 63: 'laptop', 64: 'mouse', 65: 'remote', 66: 'keyboard', 67: 'cell phone', 68: 'microwave', 69: 'oven', 70: 'toaster', 71: 'sink', 72: 'refrigerator', 73: 'book', 74: 'clock', 75: 'vase', 76: 'scissors', 77: 'teddy bear', 78: 'hair drier', 79: 'toothbrush'} obb: None orig_img: array([[[255, 255, 255], [255, 255, 255], [255, 255, 255], ..., [255, 255, 255], [255, 255, 255], [255, 255, 255]], [[255, 255, 255], [255, 255, 255], [255, 255, 255], ..., [255, 255, 255], [255, 255, 255], [255, 255, 255]], [[255, 255, 255], [255, 255, 255], [255, 255, 255], ..., [255, 255, 255], [255, 255, 255], [255, 255, 255]], ..., [[255, 255, 255], [255, 255, 255], [255, 255, 255], ..., [255, 255, 255], [255, 255, 255], [255, 255, 255]], [[255, 255, 255], [255, 255, 255], [255, 255, 255], ..., [255, 255, 255], [255, 255, 255], [255, 255, 255]], [[255, 255, 255], [255, 255, 255], [255, 255, 255], ..., [255, 255, 255], [255, 255, 255], [255, 255, 255]]], dtype=uint8) orig_shape: (1050, 679) path: 'image0.jpg' probs: None save_dir: 'runs/segment/predict' speed: {'preprocess': 1.9350051879882812, 'inference': 92.09370613098145, 'postprocess': 1.6734600067138672}], [ultralytics.engine.results.Results object with attributes: boxes: ultralytics.engine.results.Boxes object keypoints: None masks: ultralytics.engine.results.Masks object names: {0: 'person', 1: 'bicycle', 2: 'car', 3: 'motorcycle', 4: 'airplane', 5: 'bus', 6: 'train', 7: 'truck', 8: 'boat', 9: 'traffic light', 10: 'fire hydrant', 11: 'stop sign', 12: 'parking meter', 13: 'bench', 14: 'bird', 15: 'cat', 16: 'dog', 17: 'horse', 18: 'sheep', 19: 'cow', 20: 'elephant', 21: 'bear', 22: 'zebra', 23: 'giraffe', 24: 'backpack', 25: 'umbrella', 26: 'handbag', 27: 'tie', 28: 'suitcase', 29: 'frisbee', 30: 'skis', 31: 'snowboard', 32: 'sports ball', 33: 'kite', 34: 'baseball bat', 35: 'baseball glove', 36: 'skateboard', 37: 'surfboard', 38: 'tennis racket', 39: 'bottle', 40: 'wine glass', 41: 'cup', 42: 'fork', 43: 'knife', 44: 'spoon', 45: 'bowl', 46: 'banana', 47: 'apple', 48: 'sandwich', 49: 'orange', 50: 'broccoli', 51: 'carrot', 52: 'hot dog', 53: 'pizza', 54: 'donut', 55: 'cake', 56: 'chair', 57: 'couch', 58: 'potted plant', 59: 'bed', 60: 'dining table', 61: 'toilet', 62: 'tv', 63: 'laptop', 64: 'mouse', 65: 'remote', 66: 'keyboard', 67: 'cell phone', 68: 'microwave', 69: 'oven', 70: 'toaster', 71: 'sink', 72: 'refrigerator', 73: 'book', 74: 'clock', 75: 'vase', 76: 'scissors', 77: 'teddy bear', 78: 'hair drier', 79: 'toothbrush'} obb: None orig_img: array([[[255, 255, 255], [255, 255, 255], [255, 255, 255], ..., [255, 255, 255], [255, 255, 255], [255, 255, 255]], [[255, 255, 255], [255, 255, 255], [255, 255, 255], ..., [255, 255, 255], [255, 255, 255], [255, 255, 255]], [[255, 255, 255], [255, 255, 255], [255, 255, 255], ..., [255, 255, 255], [255, 255, 255], [255, 255, 255]], ..., [[255, 255, 255], [255, 255, 255], [255, 255, 255], ..., [255, 255, 255], [255, 255, 255], [255, 255, 255]], [[255, 255, 255], [255, 255, 255], [255, 255, 255], ..., [255, 255, 255], [255, 255, 255], [255, 255, 255]], [[255, 255, 255], [255, 255, 255], [255, 255, 255], ..., [255, 255, 255], [255, 255, 255], [255, 255, 255]]], dtype=uint8) orig_shape: (398, 679) path: 'image0.jpg' probs: None save_dir: 'runs/segment/predict' speed: {'preprocess': 2.300262451171875, 'inference': 89.23768997192383, 'postprocess': 1.8310546875}]] 2024-03-18 09:03:29,412 [INFO] mask_generator - Generated 5 masks 2024-03-18 09:03:29,417 [INFO] mask_generator - [[ultralytics.engine.results.Results object with attributes: boxes: ultralytics.engine.results.Boxes object keypoints: None masks: ultralytics.engine.results.Masks object names: {0: 'person', 1: 'bicycle', 2: 'car', 3: 'motorcycle', 4: 'airplane', 5: 'bus', 6: 'train', 7: 'truck', 8: 'boat', 9: 'traffic light', 10: 'fire hydrant', 11: 'stop sign', 12: 'parking meter', 13: 'bench', 14: 'bird', 15: 'cat', 16: 'dog', 17: 'horse', 18: 'sheep', 19: 'cow', 20: 'elephant', 21: 'bear', 22: 'zebra', 23: 'giraffe', 24: 'backpack', 25: 'umbrella', 26: 'handbag', 27: 'tie', 28: 'suitcase', 29: 'frisbee', 30: 'skis', 31: 'snowboard', 32: 'sports ball', 33: 'kite', 34: 'baseball bat', 35: 'baseball glove', 36: 'skateboard', 37: 'surfboard', 38: 'tennis racket', 39: 'bottle', 40: 'wine glass', 41: 'cup', 42: 'fork', 43: 'knife', 44: 'spoon', 45: 'bowl', 46: 'banana', 47: 'apple', 48: 'sandwich', 49: 'orange', 50: 'broccoli', 51: 'carrot', 52: 'hot dog', 53: 'pizza', 54: 'donut', 55: 'cake', 56: 'chair', 57: 'couch', 58: 'potted plant', 59: 'bed', 60: 'dining table', 61: 'toilet', 62: 'tv', 63: 'laptop', 64: 'mouse', 65: 'remote', 66: 'keyboard', 67: 'cell phone', 68: 'microwave', 69: 'oven', 70: 'toaster', 71: 'sink', 72: 'refrigerator', 73: 'book', 74: 'clock', 75: 'vase', 76: 'scissors', 77: 'teddy bear', 78: 'hair drier', 79: 'toothbrush'} obb: None orig_img: array([[[254, 254, 254], [254, 254, 254], [254, 254, 254], ..., [254, 254, 254], [254, 254, 254], [254, 254, 254]], [[254, 254, 254], [254, 254, 254], [254, 254, 254], ..., [254, 254, 254], [254, 254, 254], [254, 254, 254]], [[254, 254, 254], [254, 254, 254], [254, 254, 254], ..., [254, 254, 254], [254, 254, 254], [254, 254, 254]], ..., [[254, 254, 254], [254, 254, 254], [254, 254, 254], ..., [254, 254, 254], [254, 254, 254], [254, 254, 254]], [[254, 254, 254], [254, 254, 254], [254, 254, 254], ..., [254, 254, 254], [254, 254, 254], [254, 254, 254]], [[254, 254, 254], [254, 254, 254], [254, 254, 254], ..., [254, 254, 254], [254, 254, 254], [254, 254, 254]]], dtype=uint8) orig_shape: (523, 679) path: 'image0.jpg' probs: None save_dir: 'runs/segment/predict' speed: {'preprocess': 4.418849945068359, 'inference': 86.46440505981445, 'postprocess': 559.128999710083}], [ultralytics.engine.results.Results object with attributes: boxes: ultralytics.engine.results.Boxes object keypoints: None masks: ultralytics.engine.results.Masks object names: {0: 'person', 1: 'bicycle', 2: 'car', 3: 'motorcycle', 4: 'airplane', 5: 'bus', 6: 'train', 7: 'truck', 8: 'boat', 9: 'traffic light', 10: 'fire hydrant', 11: 'stop sign', 12: 'parking meter', 13: 'bench', 14: 'bird', 15: 'cat', 16: 'dog', 17: 'horse', 18: 'sheep', 19: 'cow', 20: 'elephant', 21: 'bear', 22: 'zebra', 23: 'giraffe', 24: 'backpack', 25: 'umbrella', 26: 'handbag', 27: 'tie', 28: 'suitcase', 29: 'frisbee', 30: 'skis', 31: 'snowboard', 32: 'sports ball', 33: 'kite', 34: 'baseball bat', 35: 'baseball glove', 36: 'skateboard', 37: 'surfboard', 38: 'tennis racket', 39: 'bottle', 40: 'wine glass', 41: 'cup', 42: 'fork', 43: 'knife', 44: 'spoon', 45: 'bowl', 46: 'banana', 47: 'apple', 48: 'sandwich', 49: 'orange', 50: 'broccoli', 51: 'carrot', 52: 'hot dog', 53: 'pizza', 54: 'donut', 55: 'cake', 56: 'chair', 57: 'couch', 58: 'potted plant', 59: 'bed', 60: 'dining table', 61: 'toilet', 62: 'tv', 63: 'laptop', 64: 'mouse', 65: 'remote', 66: 'keyboard', 67: 'cell phone', 68: 'microwave', 69: 'oven', 70: 'toaster', 71: 'sink', 72: 'refrigerator', 73: 'book', 74: 'clock', 75: 'vase', 76: 'scissors', 77: 'teddy bear', 78: 'hair drier', 79: 'toothbrush'} obb: None orig_img: array([[[255, 255, 255], [255, 255, 255], [255, 255, 255], ..., [255, 255, 255], [255, 255, 255], [255, 255, 255]], [[255, 255, 255], [255, 255, 255], [255, 255, 255], ..., [255, 255, 255], [255, 255, 255], [255, 255, 255]], [[255, 255, 255], [255, 255, 255], [255, 255, 255], ..., [255, 255, 255], [255, 255, 255], [255, 255, 255]], ..., [[255, 255, 255], [255, 255, 255], [255, 255, 255], ..., [255, 255, 255], [255, 255, 255], [255, 255, 255]], [[255, 255, 255], [255, 255, 255], [255, 255, 255], ..., [255, 255, 255], [255, 255, 255], [255, 255, 255]], [[255, 255, 255], [255, 255, 255], [255, 255, 255], ..., [255, 255, 255], [255, 255, 255], [255, 255, 255]]], dtype=uint8) orig_shape: (492, 679) path: 'image0.jpg' probs: None save_dir: 'runs/segment/predict' speed: {'preprocess': 2.415180206298828, 'inference': 84.3350887298584, 'postprocess': 5.3863525390625}], [ultralytics.engine.results.Results object with attributes: boxes: ultralytics.engine.results.Boxes object keypoints: None masks: ultralytics.engine.results.Masks object names: {0: 'person', 1: 'bicycle', 2: 'car', 3: 'motorcycle', 4: 'airplane', 5: 'bus', 6: 'train', 7: 'truck', 8: 'boat', 9: 'traffic light', 10: 'fire hydrant', 11: 'stop sign', 12: 'parking meter', 13: 'bench', 14: 'bird', 15: 'cat', 16: 'dog', 17: 'horse', 18: 'sheep', 19: 'cow', 20: 'elephant', 21: 'bear', 22: 'zebra', 23: 'giraffe', 24: 'backpack', 25: 'umbrella', 26: 'handbag', 27: 'tie', 28: 'suitcase', 29: 'frisbee', 30: 'skis', 31: 'snowboard', 32: 'sports ball', 33: 'kite', 34: 'baseball bat', 35: 'baseball glove', 36: 'skateboard', 37: 'surfboard', 38: 'tennis racket', 39: 'bottle', 40: 'wine glass', 41: 'cup', 42: 'fork', 43: 'knife', 44: 'spoon', 45: 'bowl', 46: 'banana', 47: 'apple', 48: 'sandwich', 49: 'orange', 50: 'broccoli', 51: 'carrot', 52: 'hot dog', 53: 'pizza', 54: 'donut', 55: 'cake', 56: 'chair', 57: 'couch', 58: 'potted plant', 59: 'bed', 60: 'dining table', 61: 'toilet', 62: 'tv', 63: 'laptop', 64: 'mouse', 65: 'remote', 66: 'keyboard', 67: 'cell phone', 68: 'microwave', 69: 'oven', 70: 'toaster', 71: 'sink', 72: 'refrigerator', 73: 'book', 74: 'clock', 75: 'vase', 76: 'scissors', 77: 'teddy bear', 78: 'hair drier', 79: 'toothbrush'} obb: None orig_img: array([[[255, 255, 255], [255, 255, 255], [255, 255, 255], ..., [255, 255, 255], [255, 255, 255], [255, 255, 255]], [[255, 255, 255], [255, 255, 255], [255, 255, 255], ..., [255, 255, 255], [255, 255, 255], [255, 255, 255]], [[255, 255, 255], [255, 255, 255], [255, 255, 255], ..., [255, 255, 255], [255, 255, 255], [255, 255, 255]], ..., [[255, 255, 255], [255, 255, 255], [255, 255, 255], ..., [255, 255, 255], [255, 255, 255], [255, 255, 255]], [[255, 255, 255], [255, 255, 255], [255, 255, 255], ..., [255, 255, 255], [255, 255, 255], [255, 255, 255]], [[255, 255, 255], [255, 255, 255], [255, 255, 255], ..., [255, 255, 255], [255, 255, 255], [255, 255, 255]]], dtype=uint8) orig_shape: (495, 679) path: 'image0.jpg' probs: None save_dir: 'runs/segment/predict' speed: {'preprocess': 2.4137496948242188, 'inference': 7.173299789428711, 'postprocess': 1.8916130065917969}], [ultralytics.engine.results.Results object with attributes: boxes: ultralytics.engine.results.Boxes object keypoints: None masks: ultralytics.engine.results.Masks object names: {0: 'person', 1: 'bicycle', 2: 'car', 3: 'motorcycle', 4: 'airplane', 5: 'bus', 6: 'train', 7: 'truck', 8: 'boat', 9: 'traffic light', 10: 'fire hydrant', 11: 'stop sign', 12: 'parking meter', 13: 'bench', 14: 'bird', 15: 'cat', 16: 'dog', 17: 'horse', 18: 'sheep', 19: 'cow', 20: 'elephant', 21: 'bear', 22: 'zebra', 23: 'giraffe', 24: 'backpack', 25: 'umbrella', 26: 'handbag', 27: 'tie', 28: 'suitcase', 29: 'frisbee', 30: 'skis', 31: 'snowboard', 32: 'sports ball', 33: 'kite', 34: 'baseball bat', 35: 'baseball glove', 36: 'skateboard', 37: 'surfboard', 38: 'tennis racket', 39: 'bottle', 40: 'wine glass', 41: 'cup', 42: 'fork', 43: 'knife', 44: 'spoon', 45: 'bowl', 46: 'banana', 47: 'apple', 48: 'sandwich', 49: 'orange', 50: 'broccoli', 51: 'carrot', 52: 'hot dog', 53: 'pizza', 54: 'donut', 55: 'cake', 56: 'chair', 57: 'couch', 58: 'potted plant', 59: 'bed', 60: 'dining table', 61: 'toilet', 62: 'tv', 63: 'laptop', 64: 'mouse', 65: 'remote', 66: 'keyboard', 67: 'cell phone', 68: 'microwave', 69: 'oven', 70: 'toaster', 71: 'sink', 72: 'refrigerator', 73: 'book', 74: 'clock', 75: 'vase', 76: 'scissors', 77: 'teddy bear', 78: 'hair drier', 79: 'toothbrush'} obb: None orig_img: array([[[255, 255, 255], [255, 255, 255], [255, 255, 255], ..., [255, 255, 255], [255, 255, 255], [255, 255, 255]], [[255, 255, 255], [255, 255, 255], [255, 255, 255], ..., [255, 255, 255], [255, 255, 255], [255, 255, 255]], [[255, 255, 255], [255, 255, 255], [255, 255, 255], ..., [255, 255, 255], [255, 255, 255], [255, 255, 255]], ..., [[255, 255, 255], [255, 255, 255], [255, 255, 255], ..., [255, 255, 255], [255, 255, 255], [255, 255, 255]], [[255, 255, 255], [255, 255, 255], [255, 255, 255], ..., [255, 255, 255], [255, 255, 255], [255, 255, 255]], [[255, 255, 255], [255, 255, 255], [255, 255, 255], ..., [255, 255, 255], [255, 255, 255], [255, 255, 255]]], dtype=uint8) orig_shape: (1050, 679) path: 'image0.jpg' probs: None save_dir: 'runs/segment/predict' speed: {'preprocess': 1.9054412841796875, 'inference': 91.08471870422363, 'postprocess': 1.6489028930664062}], [ultralytics.engine.results.Results object with attributes: boxes: ultralytics.engine.results.Boxes object keypoints: None masks: ultralytics.engine.results.Masks object names: {0: 'person', 1: 'bicycle', 2: 'car', 3: 'motorcycle', 4: 'airplane', 5: 'bus', 6: 'train', 7: 'truck', 8: 'boat', 9: 'traffic light', 10: 'fire hydrant', 11: 'stop sign', 12: 'parking meter', 13: 'bench', 14: 'bird', 15: 'cat', 16: 'dog', 17: 'horse', 18: 'sheep', 19: 'cow', 20: 'elephant', 21: 'bear', 22: 'zebra', 23: 'giraffe', 24: 'backpack', 25: 'umbrella', 26: 'handbag', 27: 'tie', 28: 'suitcase', 29: 'frisbee', 30: 'skis', 31: 'snowboard', 32: 'sports ball', 33: 'kite', 34: 'baseball bat', 35: 'baseball glove', 36: 'skateboard', 37: 'surfboard', 38: 'tennis racket', 39: 'bottle', 40: 'wine glass', 41: 'cup', 42: 'fork', 43: 'knife', 44: 'spoon', 45: 'bowl', 46: 'banana', 47: 'apple', 48: 'sandwich', 49: 'orange', 50: 'broccoli', 51: 'carrot', 52: 'hot dog', 53: 'pizza', 54: 'donut', 55: 'cake', 56: 'chair', 57: 'couch', 58: 'potted plant', 59: 'bed', 60: 'dining table', 61: 'toilet', 62: 'tv', 63: 'laptop', 64: 'mouse', 65: 'remote', 66: 'keyboard', 67: 'cell phone', 68: 'microwave', 69: 'oven', 70: 'toaster', 71: 'sink', 72: 'refrigerator', 73: 'book', 74: 'clock', 75: 'vase', 76: 'scissors', 77: 'teddy bear', 78: 'hair drier', 79: 'toothbrush'} obb: None orig_img: array([[[255, 255, 255], [255, 255, 255], [255, 255, 255], ..., [255, 255, 255], [255, 255, 255], [255, 255, 255]], [[255, 255, 255], [255, 255, 255], [255, 255, 255], ..., [255, 255, 255], [255, 255, 255], [255, 255, 255]], [[255, 255, 255], [255, 255, 255], [255, 255, 255], ..., [255, 255, 255], [255, 255, 255], [255, 255, 255]], ..., [[255, 255, 255], [255, 255, 255], [255, 255, 255], ..., [255, 255, 255], [255, 255, 255], [255, 255, 255]], [[255, 255, 255], [255, 255, 255], [255, 255, 255], ..., [255, 255, 255], [255, 255, 255], [255, 255, 255]], [[255, 255, 255], [255, 255, 255], [255, 255, 255], ..., [255, 255, 255], [255, 255, 255], [255, 255, 255]]], dtype=uint8) orig_shape: (398, 679) path: 'image0.jpg' probs: None save_dir: 'runs/segment/predict' speed: {'preprocess': 2.020120620727539, 'inference': 93.5208797454834, 'postprocess': 2.0580291748046875}]] 2024-03-18 09:04:05,461 [INFO] mask_generator - Generated 5 masks 2024-03-18 09:04:05,465 [INFO] mask_generator - [[ultralytics.engine.results.Results object with attributes: boxes: ultralytics.engine.results.Boxes object keypoints: None masks: ultralytics.engine.results.Masks object names: {0: 'person', 1: 'bicycle', 2: 'car', 3: 'motorcycle', 4: 'airplane', 5: 'bus', 6: 'train', 7: 'truck', 8: 'boat', 9: 'traffic light', 10: 'fire hydrant', 11: 'stop sign', 12: 'parking meter', 13: 'bench', 14: 'bird', 15: 'cat', 16: 'dog', 17: 'horse', 18: 'sheep', 19: 'cow', 20: 'elephant', 21: 'bear', 22: 'zebra', 23: 'giraffe', 24: 'backpack', 25: 'umbrella', 26: 'handbag', 27: 'tie', 28: 'suitcase', 29: 'frisbee', 30: 'skis', 31: 'snowboard', 32: 'sports ball', 33: 'kite', 34: 'baseball bat', 35: 'baseball glove', 36: 'skateboard', 37: 'surfboard', 38: 'tennis racket', 39: 'bottle', 40: 'wine glass', 41: 'cup', 42: 'fork', 43: 'knife', 44: 'spoon', 45: 'bowl', 46: 'banana', 47: 'apple', 48: 'sandwich', 49: 'orange', 50: 'broccoli', 51: 'carrot', 52: 'hot dog', 53: 'pizza', 54: 'donut', 55: 'cake', 56: 'chair', 57: 'couch', 58: 'potted plant', 59: 'bed', 60: 'dining table', 61: 'toilet', 62: 'tv', 63: 'laptop', 64: 'mouse', 65: 'remote', 66: 'keyboard', 67: 'cell phone', 68: 'microwave', 69: 'oven', 70: 'toaster', 71: 'sink', 72: 'refrigerator', 73: 'book', 74: 'clock', 75: 'vase', 76: 'scissors', 77: 'teddy bear', 78: 'hair drier', 79: 'toothbrush'} obb: None orig_img: array([[[254, 254, 254], [254, 254, 254], [254, 254, 254], ..., [254, 254, 254], [254, 254, 254], [254, 254, 254]], [[254, 254, 254], [254, 254, 254], [254, 254, 254], ..., [254, 254, 254], [254, 254, 254], [254, 254, 254]], [[254, 254, 254], [254, 254, 254], [254, 254, 254], ..., [254, 254, 254], [254, 254, 254], [254, 254, 254]], ..., [[254, 254, 254], [254, 254, 254], [254, 254, 254], ..., [254, 254, 254], [254, 254, 254], [254, 254, 254]], [[254, 254, 254], [254, 254, 254], [254, 254, 254], ..., [254, 254, 254], [254, 254, 254], [254, 254, 254]], [[254, 254, 254], [254, 254, 254], [254, 254, 254], ..., [254, 254, 254], [254, 254, 254], [254, 254, 254]]], dtype=uint8) orig_shape: (523, 679) path: 'image0.jpg' probs: None save_dir: 'runs/segment/predict' speed: {'preprocess': 4.465579986572266, 'inference': 87.31579780578613, 'postprocess': 623.7039566040039}], [ultralytics.engine.results.Results object with attributes: boxes: ultralytics.engine.results.Boxes object keypoints: None masks: ultralytics.engine.results.Masks object names: {0: 'person', 1: 'bicycle', 2: 'car', 3: 'motorcycle', 4: 'airplane', 5: 'bus', 6: 'train', 7: 'truck', 8: 'boat', 9: 'traffic light', 10: 'fire hydrant', 11: 'stop sign', 12: 'parking meter', 13: 'bench', 14: 'bird', 15: 'cat', 16: 'dog', 17: 'horse', 18: 'sheep', 19: 'cow', 20: 'elephant', 21: 'bear', 22: 'zebra', 23: 'giraffe', 24: 'backpack', 25: 'umbrella', 26: 'handbag', 27: 'tie', 28: 'suitcase', 29: 'frisbee', 30: 'skis', 31: 'snowboard', 32: 'sports ball', 33: 'kite', 34: 'baseball bat', 35: 'baseball glove', 36: 'skateboard', 37: 'surfboard', 38: 'tennis racket', 39: 'bottle', 40: 'wine glass', 41: 'cup', 42: 'fork', 43: 'knife', 44: 'spoon', 45: 'bowl', 46: 'banana', 47: 'apple', 48: 'sandwich', 49: 'orange', 50: 'broccoli', 51: 'carrot', 52: 'hot dog', 53: 'pizza', 54: 'donut', 55: 'cake', 56: 'chair', 57: 'couch', 58: 'potted plant', 59: 'bed', 60: 'dining table', 61: 'toilet', 62: 'tv', 63: 'laptop', 64: 'mouse', 65: 'remote', 66: 'keyboard', 67: 'cell phone', 68: 'microwave', 69: 'oven', 70: 'toaster', 71: 'sink', 72: 'refrigerator', 73: 'book', 74: 'clock', 75: 'vase', 76: 'scissors', 77: 'teddy bear', 78: 'hair drier', 79: 'toothbrush'} obb: None orig_img: array([[[255, 255, 255], [255, 255, 255], [255, 255, 255], ..., [255, 255, 255], [255, 255, 255], [255, 255, 255]], [[255, 255, 255], [255, 255, 255], [255, 255, 255], ..., [255, 255, 255], [255, 255, 255], [255, 255, 255]], [[255, 255, 255], [255, 255, 255], [255, 255, 255], ..., [255, 255, 255], [255, 255, 255], [255, 255, 255]], ..., [[255, 255, 255], [255, 255, 255], [255, 255, 255], ..., [255, 255, 255], [255, 255, 255], [255, 255, 255]], [[255, 255, 255], [255, 255, 255], [255, 255, 255], ..., [255, 255, 255], [255, 255, 255], [255, 255, 255]], [[255, 255, 255], [255, 255, 255], [255, 255, 255], ..., [255, 255, 255], [255, 255, 255], [255, 255, 255]]], dtype=uint8) orig_shape: (492, 679) path: 'image0.jpg' probs: None save_dir: 'runs/segment/predict' speed: {'preprocess': 2.6531219482421875, 'inference': 89.33091163635254, 'postprocess': 6.353139877319336}], [ultralytics.engine.results.Results object with attributes: boxes: ultralytics.engine.results.Boxes object keypoints: None masks: ultralytics.engine.results.Masks object names: {0: 'person', 1: 'bicycle', 2: 'car', 3: 'motorcycle', 4: 'airplane', 5: 'bus', 6: 'train', 7: 'truck', 8: 'boat', 9: 'traffic light', 10: 'fire hydrant', 11: 'stop sign', 12: 'parking meter', 13: 'bench', 14: 'bird', 15: 'cat', 16: 'dog', 17: 'horse', 18: 'sheep', 19: 'cow', 20: 'elephant', 21: 'bear', 22: 'zebra', 23: 'giraffe', 24: 'backpack', 25: 'umbrella', 26: 'handbag', 27: 'tie', 28: 'suitcase', 29: 'frisbee', 30: 'skis', 31: 'snowboard', 32: 'sports ball', 33: 'kite', 34: 'baseball bat', 35: 'baseball glove', 36: 'skateboard', 37: 'surfboard', 38: 'tennis racket', 39: 'bottle', 40: 'wine glass', 41: 'cup', 42: 'fork', 43: 'knife', 44: 'spoon', 45: 'bowl', 46: 'banana', 47: 'apple', 48: 'sandwich', 49: 'orange', 50: 'broccoli', 51: 'carrot', 52: 'hot dog', 53: 'pizza', 54: 'donut', 55: 'cake', 56: 'chair', 57: 'couch', 58: 'potted plant', 59: 'bed', 60: 'dining table', 61: 'toilet', 62: 'tv', 63: 'laptop', 64: 'mouse', 65: 'remote', 66: 'keyboard', 67: 'cell phone', 68: 'microwave', 69: 'oven', 70: 'toaster', 71: 'sink', 72: 'refrigerator', 73: 'book', 74: 'clock', 75: 'vase', 76: 'scissors', 77: 'teddy bear', 78: 'hair drier', 79: 'toothbrush'} obb: None orig_img: array([[[255, 255, 255], [255, 255, 255], [255, 255, 255], ..., [255, 255, 255], [255, 255, 255], [255, 255, 255]], [[255, 255, 255], [255, 255, 255], [255, 255, 255], ..., [255, 255, 255], [255, 255, 255], [255, 255, 255]], [[255, 255, 255], [255, 255, 255], [255, 255, 255], ..., [255, 255, 255], [255, 255, 255], [255, 255, 255]], ..., [[255, 255, 255], [255, 255, 255], [255, 255, 255], ..., [255, 255, 255], [255, 255, 255], [255, 255, 255]], [[255, 255, 255], [255, 255, 255], [255, 255, 255], ..., [255, 255, 255], [255, 255, 255], [255, 255, 255]], [[255, 255, 255], [255, 255, 255], [255, 255, 255], ..., [255, 255, 255], [255, 255, 255], [255, 255, 255]]], dtype=uint8) orig_shape: (495, 679) path: 'image0.jpg' probs: None save_dir: 'runs/segment/predict' speed: {'preprocess': 2.4454593658447266, 'inference': 6.887197494506836, 'postprocess': 1.6412734985351562}], [ultralytics.engine.results.Results object with attributes: boxes: ultralytics.engine.results.Boxes object keypoints: None masks: ultralytics.engine.results.Masks object names: {0: 'person', 1: 'bicycle', 2: 'car', 3: 'motorcycle', 4: 'airplane', 5: 'bus', 6: 'train', 7: 'truck', 8: 'boat', 9: 'traffic light', 10: 'fire hydrant', 11: 'stop sign', 12: 'parking meter', 13: 'bench', 14: 'bird', 15: 'cat', 16: 'dog', 17: 'horse', 18: 'sheep', 19: 'cow', 20: 'elephant', 21: 'bear', 22: 'zebra', 23: 'giraffe', 24: 'backpack', 25: 'umbrella', 26: 'handbag', 27: 'tie', 28: 'suitcase', 29: 'frisbee', 30: 'skis', 31: 'snowboard', 32: 'sports ball', 33: 'kite', 34: 'baseball bat', 35: 'baseball glove', 36: 'skateboard', 37: 'surfboard', 38: 'tennis racket', 39: 'bottle', 40: 'wine glass', 41: 'cup', 42: 'fork', 43: 'knife', 44: 'spoon', 45: 'bowl', 46: 'banana', 47: 'apple', 48: 'sandwich', 49: 'orange', 50: 'broccoli', 51: 'carrot', 52: 'hot dog', 53: 'pizza', 54: 'donut', 55: 'cake', 56: 'chair', 57: 'couch', 58: 'potted plant', 59: 'bed', 60: 'dining table', 61: 'toilet', 62: 'tv', 63: 'laptop', 64: 'mouse', 65: 'remote', 66: 'keyboard', 67: 'cell phone', 68: 'microwave', 69: 'oven', 70: 'toaster', 71: 'sink', 72: 'refrigerator', 73: 'book', 74: 'clock', 75: 'vase', 76: 'scissors', 77: 'teddy bear', 78: 'hair drier', 79: 'toothbrush'} obb: None orig_img: array([[[255, 255, 255], [255, 255, 255], [255, 255, 255], ..., [255, 255, 255], [255, 255, 255], [255, 255, 255]], [[255, 255, 255], [255, 255, 255], [255, 255, 255], ..., [255, 255, 255], [255, 255, 255], [255, 255, 255]], [[255, 255, 255], [255, 255, 255], [255, 255, 255], ..., [255, 255, 255], [255, 255, 255], [255, 255, 255]], ..., [[255, 255, 255], [255, 255, 255], [255, 255, 255], ..., [255, 255, 255], [255, 255, 255], [255, 255, 255]], [[255, 255, 255], [255, 255, 255], [255, 255, 255], ..., [255, 255, 255], [255, 255, 255], [255, 255, 255]], [[255, 255, 255], [255, 255, 255], [255, 255, 255], ..., [255, 255, 255], [255, 255, 255], [255, 255, 255]]], dtype=uint8) orig_shape: (1050, 679) path: 'image0.jpg' probs: None save_dir: 'runs/segment/predict' speed: {'preprocess': 2.025127410888672, 'inference': 88.19222450256348, 'postprocess': 1.6901493072509766}], [ultralytics.engine.results.Results object with attributes: boxes: ultralytics.engine.results.Boxes object keypoints: None masks: ultralytics.engine.results.Masks object names: {0: 'person', 1: 'bicycle', 2: 'car', 3: 'motorcycle', 4: 'airplane', 5: 'bus', 6: 'train', 7: 'truck', 8: 'boat', 9: 'traffic light', 10: 'fire hydrant', 11: 'stop sign', 12: 'parking meter', 13: 'bench', 14: 'bird', 15: 'cat', 16: 'dog', 17: 'horse', 18: 'sheep', 19: 'cow', 20: 'elephant', 21: 'bear', 22: 'zebra', 23: 'giraffe', 24: 'backpack', 25: 'umbrella', 26: 'handbag', 27: 'tie', 28: 'suitcase', 29: 'frisbee', 30: 'skis', 31: 'snowboard', 32: 'sports ball', 33: 'kite', 34: 'baseball bat', 35: 'baseball glove', 36: 'skateboard', 37: 'surfboard', 38: 'tennis racket', 39: 'bottle', 40: 'wine glass', 41: 'cup', 42: 'fork', 43: 'knife', 44: 'spoon', 45: 'bowl', 46: 'banana', 47: 'apple', 48: 'sandwich', 49: 'orange', 50: 'broccoli', 51: 'carrot', 52: 'hot dog', 53: 'pizza', 54: 'donut', 55: 'cake', 56: 'chair', 57: 'couch', 58: 'potted plant', 59: 'bed', 60: 'dining table', 61: 'toilet', 62: 'tv', 63: 'laptop', 64: 'mouse', 65: 'remote', 66: 'keyboard', 67: 'cell phone', 68: 'microwave', 69: 'oven', 70: 'toaster', 71: 'sink', 72: 'refrigerator', 73: 'book', 74: 'clock', 75: 'vase', 76: 'scissors', 77: 'teddy bear', 78: 'hair drier', 79: 'toothbrush'} obb: None orig_img: array([[[255, 255, 255], [255, 255, 255], [255, 255, 255], ..., [255, 255, 255], [255, 255, 255], [255, 255, 255]], [[255, 255, 255], [255, 255, 255], [255, 255, 255], ..., [255, 255, 255], [255, 255, 255], [255, 255, 255]], [[255, 255, 255], [255, 255, 255], [255, 255, 255], ..., [255, 255, 255], [255, 255, 255], [255, 255, 255]], ..., [[255, 255, 255], [255, 255, 255], [255, 255, 255], ..., [255, 255, 255], [255, 255, 255], [255, 255, 255]], [[255, 255, 255], [255, 255, 255], [255, 255, 255], ..., [255, 255, 255], [255, 255, 255], [255, 255, 255]], [[255, 255, 255], [255, 255, 255], [255, 255, 255], ..., [255, 255, 255], [255, 255, 255], [255, 255, 255]]], dtype=uint8) orig_shape: (398, 679) path: 'image0.jpg' probs: None save_dir: 'runs/segment/predict' speed: {'preprocess': 1.9655227661132812, 'inference': 86.20810508728027, 'postprocess': 1.8157958984375}]] 2024-03-18 09:56:51,819 [INFO] mask_generator - Segmented image 0_0 saved in the mask folder. 2024-03-18 09:56:51,831 [INFO] mask_generator - Segmented image 1_0 saved in the mask folder. 2024-03-18 09:56:51,838 [INFO] mask_generator - Segmented image 1_1 saved in the mask folder. 2024-03-18 09:56:51,846 [INFO] mask_generator - Segmented image 2_0 saved in the mask folder. 2024-03-18 09:56:51,852 [INFO] mask_generator - Segmented image 2_1 saved in the mask folder. 2024-03-18 09:56:51,864 [INFO] mask_generator - Segmented image 3_0 saved in the mask folder. 2024-03-18 09:56:51,870 [INFO] mask_generator - Segmented image 4_0 saved in the mask folder. 2024-03-18 09:58:26,908 [INFO] mask_generator - Segmented image 0_0 saved in the mask folder. 2024-03-18 09:58:26,921 [INFO] mask_generator - Segmented image 1_0 saved in the mask folder. 2024-03-18 09:58:26,927 [INFO] mask_generator - Segmented image 1_1 saved in the mask folder. 2024-03-18 09:58:26,936 [INFO] mask_generator - Segmented image 2_0 saved in the mask folder. 2024-03-18 09:58:26,942 [INFO] mask_generator - Segmented image 2_1 saved in the mask folder. 2024-03-18 09:58:26,955 [INFO] mask_generator - Segmented image 3_0 saved in the mask folder. 2024-03-18 09:58:26,962 [INFO] mask_generator - Segmented image 4_0 saved in the mask folder. 2024-03-18 10:00:04,780 [INFO] mask_generator - Segmented image 0_0 saved in the mask folder. 2024-03-18 10:00:04,793 [INFO] mask_generator - Segmented image 1_0 saved in the mask folder. 2024-03-18 10:00:04,800 [INFO] mask_generator - Segmented image 1_1 saved in the mask folder. 2024-03-18 10:00:04,808 [INFO] mask_generator - Segmented image 2_0 saved in the mask folder. 2024-03-18 10:00:04,814 [INFO] mask_generator - Segmented image 2_1 saved in the mask folder. 2024-03-18 10:00:04,827 [INFO] mask_generator - Segmented image 3_0 saved in the mask folder. 2024-03-18 10:00:04,834 [INFO] mask_generator - Segmented image 4_0 saved in the mask folder. 2024-03-18 10:00:14,923 [INFO] mask_generator - Segmented image 0 saved in the mask folder. 2024-03-18 10:00:14,936 [INFO] mask_generator - Segmented image 1 saved in the mask folder. 2024-03-18 10:00:14,944 [INFO] mask_generator - Segmented image 2 saved in the mask folder. 2024-03-18 10:00:14,958 [INFO] mask_generator - Segmented image 3 saved in the mask folder. 2024-03-18 10:00:14,965 [INFO] mask_generator - Segmented image 4 saved in the mask folder. 2024-03-18 10:00:35,536 [INFO] mask_generator - Segmented image 0 saved in the mask folder. 2024-03-18 10:00:35,549 [INFO] mask_generator - Segmented image 1 saved in the mask folder. 2024-03-18 10:00:35,557 [INFO] mask_generator - Segmented image 2 saved in the mask folder. 2024-03-18 10:00:35,571 [INFO] mask_generator - Segmented image 3 saved in the mask folder. 2024-03-18 10:00:35,578 [INFO] mask_generator - Segmented image 4 saved in the mask folder. 2024-03-19 16:21:51,598 [INFO] pipelineutils - Controlnet Pipeline initialized successfully 2024-03-19 16:22:22,911 [INFO] pipelineutils - Stable Diffusion Inpainting Pipeline initialized successfully 2024-03-20 02:42:25,744 [INFO] pipelineutils - Controlnet Pipeline initialized successfully 2024-03-20 02:43:44,812 [INFO] pipelineutils - Stable Diffusion Inpainting Pipeline initialized successfully 2024-03-20 02:56:08,862 [INFO] pipelineutils - Controlnet Pipeline initialized successfully 2024-03-20 02:56:11,147 [INFO] pipelineutils - Stable Diffusion Inpainting Pipeline initialized successfully 2024-03-20 10:38:32,329 [INFO] clear_memory - Memory Cleared 2024-03-20 10:40:01,921 [INFO] pipelineutils - Controlnet Pipeline initialized successfully 2024-03-20 10:41:30,440 [INFO] pipelineutils - Stable Diffusion Inpainting Pipeline initialized successfully 2024-03-20 10:41:30,444 [INFO] models - Inferencers initialized 2024-03-20 10:42:11,660 [INFO] clear_memory - Memory Cleared 2024-03-20 10:42:19,871 [INFO] pipelineutils - Controlnet Pipeline initialized successfully 2024-03-20 10:42:23,619 [INFO] pipelineutils - Stable Diffusion Inpainting Pipeline initialized successfully 2024-03-20 10:42:23,622 [INFO] models - Inferencers initialized 2024-03-20 10:55:18,465 [INFO] clear_memory - Memory Cleared 2024-03-20 10:55:25,336 [INFO] pipelineutils - Controlnet Pipeline initialized successfully 2024-03-20 10:55:28,411 [INFO] pipelineutils - Stable Diffusion Inpainting Pipeline initialized successfully 2024-03-20 10:55:28,413 [INFO] models - Inferencers initialized 2024-03-20 10:56:51,674 [INFO] clear_memory - Memory Cleared 2024-03-20 10:56:58,253 [INFO] pipelineutils - Controlnet Pipeline initialized successfully 2024-03-20 10:57:01,388 [INFO] pipelineutils - Stable Diffusion Inpainting Pipeline initialized successfully 2024-03-20 10:57:01,391 [INFO] models - Inferencers initialized 2024-03-20 10:57:59,104 [INFO] clear_memory - Memory Cleared 2024-03-20 10:58:06,658 [INFO] pipelineutils - Controlnet Pipeline initialized successfully 2024-03-20 10:58:10,792 [INFO] pipelineutils - Stable Diffusion Inpainting Pipeline initialized successfully 2024-03-20 10:58:10,794 [INFO] models - Inferencers initialized 2024-03-20 11:19:25,720 [INFO] clear_memory - Memory Cleared 2024-03-20 11:19:31,886 [INFO] pipelineutils - Controlnet Pipeline initialized successfully 2024-03-20 11:19:34,271 [INFO] pipelineutils - Stable Diffusion Inpainting Pipeline initialized successfully 2024-03-20 11:19:34,273 [INFO] models - Inferencers initialized 2024-03-20 11:22:23,098 [INFO] clear_memory - Memory Cleared 2024-03-20 11:22:30,208 [INFO] pipelineutils - Controlnet Pipeline initialized successfully 2024-03-20 11:22:32,810 [INFO] pipelineutils - Stable Diffusion Inpainting Pipeline initialized successfully 2024-03-20 11:22:32,816 [INFO] models - Inferencers initialized 2024-03-20 11:24:00,227 [INFO] clear_memory - Memory Cleared 2024-03-20 11:24:09,904 [INFO] pipelineutils - Controlnet Pipeline initialized successfully 2024-03-20 11:24:12,432 [INFO] pipelineutils - Stable Diffusion Inpainting Pipeline initialized successfully 2024-03-20 11:24:12,434 [INFO] models - Inferencers initialized 2024-03-20 11:25:16,562 [INFO] clear_memory - Memory Cleared 2024-03-20 11:25:22,986 [INFO] pipelineutils - Controlnet Pipeline initialized successfully 2024-03-20 11:25:25,468 [INFO] pipelineutils - Stable Diffusion Inpainting Pipeline initialized successfully 2024-03-20 11:25:25,470 [INFO] models - Inferencers initialized 2024-03-20 11:26:05,393 [INFO] clear_memory - Memory Cleared 2024-03-20 11:26:12,835 [INFO] pipelineutils - Controlnet Pipeline initialized successfully 2024-03-20 11:26:15,322 [INFO] pipelineutils - Stable Diffusion Inpainting Pipeline initialized successfully 2024-03-20 11:26:15,324 [INFO] models - Inferencers initialized 2024-03-20 11:28:02,510 [INFO] clear_memory - Memory Cleared 2024-03-20 11:28:09,082 [INFO] pipelineutils - Controlnet Pipeline initialized successfully 2024-03-20 11:28:12,138 [INFO] pipelineutils - Stable Diffusion Inpainting Pipeline initialized successfully 2024-03-20 11:28:12,140 [INFO] models - Inferencers initialized 2024-03-20 11:30:00,417 [INFO] clear_memory - Memory Cleared 2024-03-20 11:30:10,075 [INFO] pipelineutils - Controlnet Pipeline initialized successfully 2024-03-20 11:30:13,193 [INFO] pipelineutils - Stable Diffusion Inpainting Pipeline initialized successfully 2024-03-20 11:30:13,195 [INFO] models - Inferencers initialized 2024-03-20 11:31:09,394 [INFO] clear_memory - Memory Cleared 2024-03-20 11:31:17,250 [INFO] pipelineutils - Controlnet Pipeline initialized successfully 2024-03-20 11:31:21,524 [INFO] pipelineutils - Stable Diffusion Inpainting Pipeline initialized successfully 2024-03-20 11:31:21,526 [INFO] models - Inferencers initialized 2024-03-20 11:35:08,035 [INFO] clear_memory - Memory Cleared 2024-03-20 11:35:14,954 [INFO] pipelineutils - Controlnet Pipeline initialized successfully 2024-03-20 11:35:17,989 [INFO] pipelineutils - Stable Diffusion Inpainting Pipeline initialized successfully 2024-03-20 11:35:17,991 [INFO] models - Inferencers initialized 2024-03-20 11:36:39,721 [INFO] clear_memory - Memory Cleared 2024-03-20 11:36:47,941 [INFO] pipelineutils - Controlnet Pipeline initialized successfully 2024-03-20 11:36:50,750 [INFO] pipelineutils - Stable Diffusion Inpainting Pipeline initialized successfully 2024-03-20 11:36:50,754 [INFO] models - Inferencers initialized 2024-03-20 11:39:05,892 [INFO] clear_memory - Memory Cleared 2024-03-20 11:39:12,522 [INFO] pipelineutils - Controlnet Pipeline initialized successfully 2024-03-20 11:39:16,221 [INFO] pipelineutils - Stable Diffusion Inpainting Pipeline initialized successfully 2024-03-20 11:39:16,225 [INFO] models - Inferencers initialized 2024-03-20 11:47:31,153 [INFO] mask_generator - Memory Cleared 2024-03-20 11:53:21,318 [INFO] mask_generator - Memory Cleared 2024-03-20 11:54:26,182 [INFO] mask_generator - Memory Cleared 2024-03-20 11:55:53,548 [INFO] mask_generator - Memory Cleared 2024-03-20 11:56:59,724 [INFO] mask_generator - Memory Cleared 2024-03-20 11:58:24,546 [INFO] mask_generator - Memory Cleared 2024-03-20 12:22:46,335 [INFO] pipelineutils - Controlnet Pipeline initialized successfully 2024-03-20 12:22:49,307 [INFO] pipelineutils - Stable Diffusion Inpainting Pipeline initialized successfully 2024-03-20 12:22:49,309 [INFO] models - Inferencers initialized 2024-03-20 12:24:43,513 [INFO] pipelineutils - Controlnet Pipeline initialized successfully 2024-03-20 12:24:46,607 [INFO] pipelineutils - Stable Diffusion Inpainting Pipeline initialized successfully 2024-03-20 12:24:46,609 [INFO] models - Inferencers initialized 2024-03-20 12:30:52,791 [INFO] pipelineutils - Controlnet Pipeline initialized successfully 2024-03-20 12:30:56,540 [INFO] pipelineutils - Stable Diffusion Inpainting Pipeline initialized successfully 2024-03-20 12:30:56,542 [INFO] models - Inferencers initialized 2024-03-20 12:34:45,035 [INFO] pipelineutils - Controlnet Pipeline initialized successfully 2024-03-20 12:34:49,750 [INFO] pipelineutils - Stable Diffusion Inpainting Pipeline initialized successfully 2024-03-20 12:34:49,752 [INFO] models - Inferencers initialized 2024-03-20 12:35:23,559 [INFO] pipelineutils - Controlnet Pipeline initialized successfully 2024-03-20 12:35:26,118 [INFO] pipelineutils - Stable Diffusion Inpainting Pipeline initialized successfully 2024-03-20 12:35:26,119 [INFO] models - Inferencers initialized 2024-03-20 12:36:43,460 [INFO] pipelineutils - Controlnet Pipeline initialized successfully 2024-03-20 12:36:46,852 [INFO] pipelineutils - Stable Diffusion Inpainting Pipeline initialized successfully 2024-03-20 12:36:46,855 [INFO] models - Inferencers initialized 2024-03-20 12:42:00,556 [INFO] pipelineutils - Controlnet Pipeline initialized successfully 2024-03-20 12:42:04,338 [INFO] pipelineutils - Stable Diffusion Inpainting Pipeline initialized successfully 2024-03-20 12:42:04,344 [INFO] models - Inferencers initialized 2024-03-20 12:42:38,211 [INFO] pipelineutils - Controlnet Pipeline initialized successfully 2024-03-20 12:42:41,170 [INFO] pipelineutils - Stable Diffusion Inpainting Pipeline initialized successfully 2024-03-20 12:42:41,172 [INFO] models - Inferencers initialized 2024-03-20 13:41:54,179 [INFO] pipelineutils - Controlnet Pipeline initialized successfully 2024-03-20 13:41:57,017 [INFO] pipelineutils - Stable Diffusion Inpainting Pipeline initialized successfully 2024-03-20 13:41:57,019 [INFO] models - Inferencers initialized 2024-03-20 13:44:04,422 [INFO] pipelineutils - Controlnet Pipeline initialized successfully 2024-03-20 13:44:07,139 [INFO] pipelineutils - Stable Diffusion Inpainting Pipeline initialized successfully 2024-03-20 13:44:07,141 [INFO] models - Inferencers initialized 2024-03-20 13:46:25,331 [INFO] pipelineutils - Controlnet Pipeline initialized successfully 2024-03-20 13:46:27,936 [INFO] pipelineutils - Stable Diffusion Inpainting Pipeline initialized successfully 2024-03-20 13:46:27,938 [INFO] models - Inferencers initialized 2024-03-20 13:47:06,813 [INFO] pipelineutils - Controlnet Pipeline initialized successfully 2024-03-20 13:47:09,623 [INFO] pipelineutils - Stable Diffusion Inpainting Pipeline initialized successfully 2024-03-20 13:47:09,625 [INFO] models - Inferencers initialized 2024-03-20 13:47:37,535 [INFO] pipelineutils - Controlnet Pipeline initialized successfully 2024-03-20 13:47:40,252 [INFO] pipelineutils - Stable Diffusion Inpainting Pipeline initialized successfully 2024-03-20 13:47:40,254 [INFO] models - Inferencers initialized 2024-03-20 13:48:35,425 [INFO] pipelineutils - Controlnet Pipeline initialized successfully 2024-03-20 13:48:38,307 [INFO] pipelineutils - Stable Diffusion Inpainting Pipeline initialized successfully 2024-03-20 13:48:38,312 [INFO] models - Inferencers initialized 2024-03-20 13:50:48,735 [INFO] pipelineutils - Controlnet Pipeline initialized successfully 2024-03-20 13:50:51,801 [INFO] pipelineutils - Stable Diffusion Inpainting Pipeline initialized successfully 2024-03-20 13:50:51,805 [INFO] models - Inferencers initialized 2024-03-20 13:51:24,249 [INFO] pipelineutils - Controlnet Pipeline initialized successfully 2024-03-20 13:51:28,192 [INFO] pipelineutils - Stable Diffusion Inpainting Pipeline initialized successfully 2024-03-20 13:51:28,198 [INFO] models - Inferencers initialized 2024-03-20 13:55:08,230 [INFO] pipelineutils - Controlnet Pipeline initialized successfully 2024-03-20 13:55:10,645 [INFO] pipelineutils - Stable Diffusion Inpainting Pipeline initialized successfully 2024-03-20 13:55:10,647 [INFO] models - Inferencers initialized 2024-03-20 13:55:50,797 [INFO] pipelineutils - Controlnet Pipeline initialized successfully 2024-03-20 13:55:54,600 [INFO] pipelineutils - Stable Diffusion Inpainting Pipeline initialized successfully 2024-03-20 13:55:54,602 [INFO] models - Inferencers initialized 2024-03-20 13:57:04,195 [INFO] pipelineutils - Controlnet Pipeline initialized successfully 2024-03-20 13:57:06,633 [INFO] pipelineutils - Stable Diffusion Inpainting Pipeline initialized successfully 2024-03-20 13:57:06,635 [INFO] models - Inferencers initialized 2024-03-20 14:01:03,804 [INFO] pipelineutils - Controlnet Pipeline initialized successfully 2024-03-20 14:01:06,295 [INFO] pipelineutils - Stable Diffusion Inpainting Pipeline initialized successfully 2024-03-20 14:01:06,297 [INFO] models - Inferencers initialized 2024-03-20 14:02:26,320 [INFO] pipelineutils - Controlnet Pipeline initialized successfully 2024-03-20 14:02:29,742 [INFO] pipelineutils - Stable Diffusion Inpainting Pipeline initialized successfully 2024-03-20 14:02:29,746 [INFO] models - Inferencers initialized 2024-03-20 14:04:39,507 [INFO] pipelineutils - Controlnet Pipeline initialized successfully 2024-03-20 14:04:42,180 [INFO] pipelineutils - Stable Diffusion Inpainting Pipeline initialized successfully 2024-03-20 14:04:42,184 [INFO] models - Inferencers initialized 2024-03-20 14:10:27,388 [INFO] pipelineutils - Controlnet Pipeline initialized successfully 2024-03-20 14:10:30,038 [INFO] pipelineutils - Stable Diffusion Inpainting Pipeline initialized successfully 2024-03-20 14:10:30,040 [INFO] models - Inferencers initialized 2024-03-20 14:18:22,594 [INFO] pipelineutils - Controlnet Pipeline initialized successfully 2024-03-20 14:18:25,364 [INFO] pipelineutils - Stable Diffusion Inpainting Pipeline initialized successfully 2024-03-20 14:18:25,369 [INFO] models - Inferencers initialized 2024-03-20 14:23:36,396 [INFO] pipelineutils - Controlnet Pipeline initialized successfully 2024-03-20 14:23:38,981 [INFO] pipelineutils - Stable Diffusion Inpainting Pipeline initialized successfully 2024-03-20 14:23:38,985 [INFO] models - Inferencers initialized 2024-03-20 14:30:42,487 [INFO] pipelineutils - Controlnet Pipeline initialized successfully 2024-03-20 14:30:44,732 [INFO] pipelineutils - Stable Diffusion Inpainting Pipeline initialized successfully 2024-03-20 14:30:44,736 [INFO] models - Inferencers initialized 2024-03-20 14:33:08,425 [INFO] pipelineutils - Controlnet Pipeline initialized successfully 2024-03-20 14:33:10,763 [INFO] pipelineutils - Stable Diffusion Inpainting Pipeline initialized successfully 2024-03-20 14:33:40,278 [INFO] pipelineutils - Controlnet Pipeline initialized successfully 2024-03-20 14:33:43,138 [INFO] pipelineutils - Stable Diffusion Inpainting Pipeline initialized successfully 2024-03-20 14:42:52,447 [INFO] pipelineutils - Controlnet Pipeline initialized successfully 2024-03-20 14:42:55,325 [INFO] pipelineutils - Stable Diffusion Inpainting Pipeline initialized successfully 2024-03-20 14:43:53,817 [INFO] pipelineutils - Controlnet Pipeline initialized successfully 2024-03-20 14:43:56,436 [INFO] pipelineutils - Stable Diffusion Inpainting Pipeline initialized successfully 2024-03-20 14:45:15,158 [INFO] pipelineutils - Controlnet Pipeline initialized successfully 2024-03-20 14:45:17,668 [INFO] pipelineutils - Stable Diffusion Inpainting Pipeline initialized successfully 2024-03-20 14:47:17,389 [INFO] pipelineutils - Controlnet Pipeline initialized successfully 2024-03-20 14:47:19,932 [INFO] pipelineutils - Stable Diffusion Inpainting Pipeline initialized successfully 2024-03-20 14:49:27,306 [INFO] pipelineutils - Controlnet Pipeline initialized successfully 2024-03-20 14:49:30,392 [INFO] pipelineutils - Stable Diffusion Inpainting Pipeline initialized successfully 2024-03-20 14:50:57,968 [INFO] pipelineutils - Controlnet Pipeline initialized successfully 2024-03-20 14:51:00,601 [INFO] pipelineutils - Stable Diffusion Inpainting Pipeline initialized successfully 2024-03-20 14:51:36,287 [INFO] pipelineutils - Controlnet Pipeline initialized successfully 2024-03-20 14:51:38,790 [INFO] pipelineutils - Stable Diffusion Inpainting Pipeline initialized successfully 2024-03-20 14:57:38,141 [INFO] pipelineutils - Controlnet Pipeline initialized successfully 2024-03-20 14:57:41,881 [INFO] pipelineutils - Stable Diffusion Inpainting Pipeline initialized successfully 2024-03-20 14:58:36,535 [INFO] pipelineutils - Controlnet Pipeline initialized successfully 2024-03-20 14:58:40,114 [INFO] pipelineutils - Stable Diffusion Inpainting Pipeline initialized successfully 2024-03-20 15:00:27,677 [INFO] pipelineutils - Controlnet Pipeline initialized successfully 2024-03-20 15:00:30,158 [INFO] pipelineutils - Stable Diffusion Inpainting Pipeline initialized successfully 2024-03-20 15:01:15,550 [INFO] pipelineutils - Controlnet Pipeline initialized successfully 2024-03-20 15:01:19,435 [INFO] pipelineutils - Stable Diffusion Inpainting Pipeline initialized successfully 2024-03-20 15:06:07,192 [INFO] pipelineutils - Controlnet Pipeline initialized successfully 2024-03-20 15:06:09,637 [INFO] pipelineutils - Stable Diffusion Inpainting Pipeline initialized successfully 2024-03-20 15:08:38,745 [INFO] pipelineutils - Controlnet Pipeline initialized successfully 2024-03-20 15:08:41,349 [INFO] pipelineutils - Stable Diffusion Inpainting Pipeline initialized successfully 2024-03-20 15:15:47,402 [INFO] pipelineutils - Controlnet Pipeline initialized successfully 2024-03-20 15:15:49,983 [INFO] pipelineutils - Stable Diffusion Inpainting Pipeline initialized successfully 2024-03-20 15:17:00,769 [INFO] pipelineutils - Controlnet Pipeline initialized successfully 2024-03-20 15:17:04,001 [INFO] pipelineutils - Stable Diffusion Inpainting Pipeline initialized successfully 2024-03-20 15:17:43,382 [INFO] pipelineutils - Controlnet Pipeline initialized successfully 2024-03-20 15:17:46,223 [INFO] pipelineutils - Stable Diffusion Inpainting Pipeline initialized successfully 2024-03-20 15:27:45,777 [INFO] pipelineutils - Controlnet Pipeline initialized successfully 2024-03-20 15:27:48,514 [INFO] pipelineutils - Stable Diffusion Inpainting Pipeline initialized successfully 2024-03-20 15:30:41,667 [INFO] pipelineutils - Controlnet Pipeline initialized successfully 2024-03-20 15:30:44,567 [INFO] pipelineutils - Stable Diffusion Inpainting Pipeline initialized successfully 2024-03-20 16:38:38,658 [INFO] pipelineutils - Controlnet Pipeline initialized successfully 2024-03-20 16:39:19,333 [INFO] pipelineutils - Controlnet Pipeline initialized successfully 2024-03-20 16:39:50,404 [INFO] pipelineutils - Controlnet Pipeline initialized successfully 2024-03-20 16:45:37,037 [INFO] pipelineutils - Controlnet Pipeline initialized successfully 2024-03-22 03:55:40,678 [INFO] models - Inpainting Inference 2024-03-22 03:55:41,174 [INFO] clear_memory - Memory Cleared 2024-03-22 03:58:06,886 [INFO] models - Inpainting Inference 2024-03-22 03:58:07,066 [INFO] clear_memory - Memory Cleared 2024-03-22 04:01:27,172 [INFO] models - Inpainting Inference 2024-03-22 04:01:27,418 [INFO] clear_memory - Memory Cleared 2024-03-22 04:06:38,680 [INFO] models - Inpainting Inference 2024-03-22 04:06:38,889 [INFO] clear_memory - Memory Cleared 2024-03-22 04:11:41,673 [INFO] models - Inpainting Inference 2024-03-22 04:11:41,874 [INFO] clear_memory - Memory Cleared 2024-03-22 04:20:36,838 [INFO] models - Inpainting Inference Completed 2024-03-22 04:30:50,234 [INFO] models - Inpainting Inference 2024-03-22 04:30:50,522 [INFO] clear_memory - Memory Cleared 2024-03-22 04:34:30,860 [INFO] models - Inpainting Inference Completed 2024-03-22 04:37:41,028 [INFO] models - Inpainting Inference 2024-03-22 04:38:16,111 [INFO] models - Inpainting Inference 2024-03-22 04:38:16,367 [INFO] clear_memory - Memory Cleared 2024-03-22 04:40:29,119 [INFO] models - Inpainting Inference Completed 2024-03-22 05:00:56,937 [INFO] models - Kandinsky Inpainting Inference 2024-03-22 05:02:34,916 [INFO] models - Kandinsky Inpainting Inference 2024-03-22 05:13:44,547 [INFO] models - Kandinsky Inpainting Inference 2024-03-22 05:18:53,623 [INFO] models - Inpainting Inference Completed 2024-03-22 05:20:06,892 [INFO] models - Kandinsky Inpainting Inference 2024-03-22 05:20:26,852 [INFO] models - Inpainting Inference Completed 2024-03-22 05:25:49,956 [INFO] models - Kandinsky Inpainting Inference 2024-03-22 05:26:09,324 [INFO] models - Inpainting Inference Completed 2024-03-22 05:26:58,013 [INFO] models - Kandinsky Inpainting Inference 2024-03-22 05:27:17,153 [INFO] models - Inpainting Inference Completed 2024-03-22 05:32:55,633 [INFO] models - Kandinsky Inpainting Inference 2024-03-22 05:33:14,930 [INFO] models - Inpainting Inference Completed 2024-03-22 05:33:47,613 [INFO] models - Kandinsky Inpainting Inference 2024-03-22 05:34:06,803 [INFO] models - Inpainting Inference Completed 2024-03-22 05:34:56,622 [INFO] models - Kandinsky Inpainting Inference 2024-03-22 05:35:16,304 [INFO] models - Inpainting Inference Completed 2024-03-22 05:37:23,678 [INFO] models - Kandinsky Inpainting Inference 2024-03-22 05:37:46,172 [INFO] models - Inpainting Inference Completed 2024-03-22 06:04:47,683 [INFO] models - Kandinsky Inpainting Inference 2024-03-22 06:09:12,886 [INFO] models - Kandinsky Inpainting Inference 2024-03-22 06:12:29,146 [INFO] models - Kandinsky Inpainting Inference 2024-03-22 06:24:32,044 [INFO] models - Kandinsky Inpainting Inference 2024-03-22 06:27:52,332 [INFO] models - Kandinsky Inpainting Inference 2024-03-22 06:35:16,527 [INFO] models - Kandinsky Inpainting Inference 2024-03-22 06:39:26,709 [INFO] models - Kandinsky Inpainting Inference 2024-03-22 06:43:26,086 [INFO] models - Kandinsky Inpainting Inference 2024-03-22 06:53:54,562 [INFO] models - Kandinsky Inpainting Inference 2024-03-22 07:03:17,990 [INFO] models - Kandinsky Inpainting Inference 2024-03-22 07:09:38,955 [INFO] models - Kandinsky Inpainting Inference 2024-03-22 07:17:59,975 [INFO] models - Kandinsky Inpainting Inference 2024-03-22 07:28:54,339 [INFO] models - Kandinsky Inpainting Inference 2024-03-22 07:41:45,300 [INFO] models - Kandinsky Inpainting Inference 2024-03-22 07:50:46,880 [INFO] models - Kandinsky Inpainting Inference 2024-03-22 08:05:52,674 [INFO] models - Kandinsky Inpainting Inference 2024-03-22 08:11:07,093 [INFO] models - Kandinsky Inpainting Inference 2024-03-22 08:49:32,092 [INFO] models - Kandinsky Inpainting Inference 2024-03-22 08:56:43,084 [INFO] models - Kandinsky Inpainting Inference 2024-03-22 09:13:03,681 [INFO] models - Kandinsky Inpainting Inference 2024-03-22 09:23:45,335 [INFO] models - Kandinsky Inpainting Inference 2024-03-22 09:29:54,960 [INFO] models - Kandinsky Inpainting Inference 2024-03-22 09:31:28,680 [INFO] models - Kandinsky Inpainting Inference 2024-03-22 09:39:32,351 [INFO] models - Kandinsky Inpainting Inference 2024-03-22 09:47:05,180 [INFO] models - Kandinsky Inpainting Inference 2024-03-22 09:51:28,523 [INFO] models - Kandinsky Inpainting Inference 2024-03-22 09:53:18,039 [INFO] models - Kandinsky Inpainting Inference <<<<<<< HEAD ======= 2024-03-23 08:26:37,691 [INFO] mask_generator - Mask generation completed successfully 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mask_generator - Mask generation completed successfully 2024-03-23 10:07:32,135 [INFO] mask_generator - Mask generation completed successfully 2024-03-23 11:02:29,843 [INFO] mask_generator - Mask generation completed successfully 2024-03-23 11:05:02,471 [INFO] mask_generator - Mask generation completed successfully 2024-03-23 19:23:38,952 [INFO] clear_memory - Memory Cleared 2024-03-23 19:42:39,347 [INFO] clear_memory - Memory Cleared 2024-03-24 12:51:21,021 [INFO] clear_memory - Memory Cleared 2024-03-24 13:07:46,765 [INFO] clear_memory - Memory Cleared 2024-03-24 13:14:03,557 [INFO] clear_memory - Memory Cleared 2024-03-24 13:17:25,009 [INFO] clear_memory - Memory Cleared 2024-03-24 13:23:11,117 [INFO] clear_memory - Memory Cleared 2024-03-24 13:28:30,138 [INFO] clear_memory - Memory Cleared 2024-03-24 13:32:00,626 [INFO] clear_memory - Memory Cleared 2024-03-24 13:35:18,404 [INFO] clear_memory - Memory Cleared 2024-03-24 13:38:37,096 [INFO] clear_memory - Memory Cleared 2024-03-24 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Cleared 2024-03-24 20:30:39,800 [INFO] clear_memory - Memory Cleared 2024-03-24 20:37:12,153 [INFO] clear_memory - Memory Cleared 2024-03-24 20:42:47,710 [INFO] clear_memory - Memory Cleared 2024-03-24 20:48:23,383 [INFO] clear_memory - Memory Cleared 2024-03-24 20:56:31,162 [INFO] clear_memory - Memory Cleared 2024-03-24 21:03:44,503 [INFO] clear_memory - Memory Cleared 2024-03-24 21:09:56,651 [INFO] clear_memory - Memory Cleared 2024-03-24 21:17:23,320 [INFO] clear_memory - Memory Cleared 2024-03-24 21:23:06,580 [INFO] clear_memory - Memory Cleared 2024-03-24 21:29:14,870 [INFO] clear_memory - Memory Cleared 2024-03-24 21:36:09,328 [INFO] clear_memory - Memory Cleared 2024-03-24 21:40:40,507 [INFO] clear_memory - Memory Cleared 2024-03-24 21:44:47,907 [INFO] clear_memory - Memory Cleared 2024-03-24 21:48:43,724 [INFO] clear_memory - Memory Cleared 2024-03-24 21:52:50,583 [INFO] clear_memory - Memory Cleared 2024-03-26 19:58:18,622 [INFO] clear_memory - Memory Cleared 2024-03-26 19:58:18,633 [INFO] models - I2VGenXL pipeline Inference -> 2024-03-26 20:22:04,466 [INFO] clear_memory - Memory Cleared 2024-03-26 20:22:04,471 [INFO] models - Stable Video Diffusion Image 2 Video pipeline Inference -> >>>>>>> 7dce291 (Update image and video pipelines)