oven-lab / tuya_cloud_map_extractor

Tuya cloud vacuum map extractor for Home Assistant
MIT License
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[BUG] LuBlueLu SL60D - Error Getting Path #41

Open iamjmitch opened 6 months ago

iamjmitch commented 6 months ago

V1.2.0 LuBlueLu SL60D Firmware: 2.6.46 MCU: 15.0.25

Having issues with "Show Path" on LuBlueLu SL60D. If I dont select "Show Path" when configuring the map loads fine however when i click "Show Path" i get no map. checking the logs i get the following error:

2024-05-18 16:03:59.685 DEBUG (MainThread) [custom_components.tuya_cloud_map_extractor.camera] Async setup entry

2024-05-18 16:03:59.685 DEBUG (MainThread) [custom_components.tuya_cloud_map_extractor.camera] Adding entities

2024-05-18 16:03:59.685 DEBUG (MainThread) [custom_components.tuya_cloud_map_extractor.camera] Init camera

2024-05-18 16:03:59.686 DEBUG (MainThread) [custom_components.tuya_cloud_map_extractor.camera] Fetching state

2024-05-18 16:03:59.687 DEBUG (MainThread) [custom_components.tuya_cloud_map_extractor.camera] Done

2024-05-18 16:03:59.690 DEBUG (SyncWorker_42) [custom_components.tuya_cloud_map_extractor.camera] Getting map

2024-05-18 16:04:03.870 DEBUG (SyncWorker_42) [custom_components.tuya_cloud_map_extractor.tuya_vacuum_map_extractor.main] Response: 200b'AA.....(a whole bunch of letters/numbers here)

2024-05-18 16:04:03.871 DEBUG (SyncWorker_42) [custom_components.tuya_cloud_map_extractor.tuya_vacuum_map_extractor.v1] {'id': [5], 'version': [1], 'roomeditable': True, 'type': [1], 'width': 322, 'height': 517, 'originx': 1600, 'originy': 2890, 'mapResolution': 4, 'pileX': 1780, 'pileY': 3940, 'totalcount': 166617, 'compressbeforelength': 166617, 'compressafterlenght': 12570, 'calibrationPoints': [{'vacuum': {'x': 0, 'y': 0}, 'map': {'x': 0.0, 'y': -0.0}}, {'vacuum': {'x': 0, 'y': 200}, 'map': {'x': 0.0, 'y': -20.0}}, {'vacuum': {'x': 200, 'y': 0}, 'map': {'x': 20.0, 'y': -0.0}}]}

2024-05-18 16:04:03.991 DEBUG (SyncWorker_42) [custom_components.tuya_cloud_map_extractor.tuya_vacuum_map_extractor.main] Rendering path

2024-05-18 16:04:05.080 DEBUG (SyncWorker_42) [custom_components.tuya_cloud_map_extractor.tuya_vacuum_map_extractor.main] Response path: 200b.....(a whole bunch of letters/numbers here)

2024-05-18 16:04:05.103 ERROR (SyncWorker_42) [custom_components.tuya_cloud_map_extractor.tuya_vacuum_map_extractor.main] Failed to parse path: b'AAGfAAIAAAYrAAAWboX.....(a whole bunch of letters/numbers here)

2024-05-18 16:04:05.103 WARNING (SyncWorker_42) [custom_components.tuya_cloud_map_extractor.camera] Unable to parse map data

2024-05-18 16:04:05.103 ERROR (SyncWorker_42) [custom_components.tuya_cloud_map_extractor.camera] not enough values to unpack (expected 2, got 1)

2024-05-18 16:04:05.107 DEBUG (MainThread) [custom_components.tuya_cloud_map_extractor.camera] Fetching state

Full Error Log path error.txt

reef-actor commented 6 months ago

Adding my logs for the same issue with this model

HA log 1 "Failed to parse path" Failed to parse path: b'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'
HA log 2 "not enough values to unpack (expected 2, got 1)" ``` not enough values to unpack (expected 2, got 1) Traceback (most recent call last): File "/usr/local/lib/python3.12/site-packages/requests/models.py", line 971, in json return complexjson.loads(self.text, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/usr/local/lib/python3.12/site-packages/simplejson/__init__.py", line 514, in loads return _default_decoder.decode(s) ^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/usr/local/lib/python3.12/site-packages/simplejson/decoder.py", line 386, in decode obj, end = self.raw_decode(s) ^^^^^^^^^^^^^^^^^^ File "/usr/local/lib/python3.12/site-packages/simplejson/decoder.py", line 416, in raw_decode return self.scan_once(s, idx=_w(s, idx).end()) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ simplejson.errors.JSONDecodeError: Expecting value: line 1 column 1 (char 0) During handling of the above exception, another exception occurred: Traceback (most recent call last): File "/config/custom_components/tuya_cloud_map_extractor/tuya_vacuum_map_extractor/main.py", line 47, in parse_path data = response.json() ^^^^^^^^^^^^^^^ File "/usr/local/lib/python3.12/site-packages/requests/models.py", line 975, in json raise RequestsJSONDecodeError(e.msg, e.doc, e.pos) requests.exceptions.JSONDecodeError: Expecting value: line 1 column 1 (char 0) During handling of the above exception, another exception occurred: Traceback (most recent call last): File "/config/custom_components/tuya_cloud_map_extractor/config_flow.py", line 57, in async_step_user headers, image = await validate(self.hass, user_input) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/config/custom_components/tuya_cloud_map_extractor/config_flow.py", line 214, in validate return await hass.async_add_executor_job( ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/usr/local/lib/python3.12/concurrent/futures/thread.py", line 58, in run result = self.fn(*self.args, **self.kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/config/custom_components/tuya_cloud_map_extractor/tuya_vacuum_map_extractor/main.py", line 192, in get_map raise e File "/config/custom_components/tuya_cloud_map_extractor/tuya_vacuum_map_extractor/main.py", line 189, in get_map path = parse_path(response, scale=scale, header=header) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/config/custom_components/tuya_cloud_map_extractor/tuya_vacuum_map_extractor/main.py", line 51, in parse_path path_data = decode_path_v1(data) ^^^^^^^^^^^^^^^^^^^^ File "/config/custom_components/tuya_cloud_map_extractor/tuya_vacuum_map_extractor/v1.py", line 111, in decode_path_v1 x, y = [_deal_pl(_highLowToInt(high, low)) for high, low in _partition(point, 2)] ^^^^^^^^^ ValueError: not enough values to unpack (expected 2, got 1) ```
reef-actor commented 6 months ago

The error is avoided by adding a check for len(point) == 4 to the for point in path_data_arr in v1.py (last point has len == 1)

Perfect 🙃

Dump of some data

pathdata ``` 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```
path_data_arr ``` [[243, 3, 1, 154], [4, 7, 1, 134], [4, 7, 1, 84], [4, 7, 1, 64], [4, 7, 1, 74], [12, 0, 241, 146], [94, 4, 7, 1], [44, 3, 53, 1], [14, 1, 135, 1], [14, 1, 95, 1], [4, 0, 121, 1], [4, 0, 81, 1], [4, 255, 107, 1], [4, 255, 67, 1], [4, 255, 27, 1], [14, 254, 243, 1], [14, 254, 13, 1], [24, 253, 229, 1], [24, 252, 255, 1], [24, 252, 215, 1], [24, 252, 175, 1], [34, 252, 135, 1], [34, 252, 95, 1], [34, 252, 55, 1], [34, 252, 15, 1], [44, 251, 241, 1], [44, 251, 201, 1], [44, 251, 161, 1], [44, 251, 121, 1], [44, 251, 100, 1], [34, 251, 90, 1], [24, 251, 80, 1], [24, 251, 70, 1], [14, 251, 50, 0], [240, 251, 30, 0], [210, 251, 30, 0], [180, 251, 30, 0], [170, 251, 30, 0], [160, 251, 20, 0], [160, 251, 10, 0], [170, 251, 10, 0], [160, 250, 246, 0], [160, 250, 236, 0], [160, 250, 226, 0], [160, 250, 206, 0], [150, 250, 196, 0], [150, 8, 0, 241], [12, 186, 0, 150], [250, 146, 0, 150], [250, 136, 0, 150], [250, 116, 0, 150], [250, 106, 0, 160], [250, 86, 0, 160], [250, 56, 0, 170], [4, 0, 241, 108], [46, 0, 190, 250], [46, 0, 220, 250], [46, 0, 250, 250], [36, 1, 4, 250], [16, 1, 14, 250], [6, 1, 4, 250], [6, 1, 24, 249], [252, 1, 54, 249], [252, 1, 84, 249], [252, 1, 124, 249], [252, 1, 144, 249], [252, 1, 154, 250], [26, 1, 164, 250], [46, 1, 194, 250], [56, 1, 234, 250], [46, 1, 254, 250], [46, 1, 244, 250], [66, 1, 244, 250], [106, 1, 254, 250], [136, 1, 244, 250], [146, 1, 244, 251], [30, 1, 224, 251], [30, 1, 204, 251], [30, 1, 174, 251], [40, 1, 164, 251], [60, 1, 154, 251], [90, 1, 154, 251], [100, 1, 124, 251], [110, 1, 84, 251], [110, 1, 44, 251], [120, 1, 34, 4], [0, 113, 110, 1], [24, 251, 90, 1], [14, 4, 0, 240], [24, 60, 1, 4], [251, 40, 1, 14], [251, 30, 1, 14], [250, 246, 1, 14], [250, 196, 1, 14], [250, 146, 1, 14], [250, 96, 1, 14], [250, 56, 1, 4], [250, 36, 0, 230], [250, 56, 0, 240], [4, 0, 128, 251], [10, 0, 220, 251], [10, 0, 210, 4], [0, 240, 133, 250], [226, 0, 210, 250], [186, 0, 210, 250], [126, 0, 210, 250], [96, 0, 210, 250], [76, 0, 200, 250], [66, 0, 190, 250], [66, 0, 180, 250], [76, 0, 180, 250], [126, 0, 180, 250], [176, 0, 180, 250], [236, 0, 180, 251], [0, 0, 170, 251], [11, 0, 180, 251], [11, 0, 220, 251], [11, 1, 4, 251], [1, 1, 34, 250], [247, 1, 44, 251], [1, 1, 44, 251], [21, 1, 44, 251], [71, 1, 44, 251], [80, 1, 44, 250], [56, 1, 44, 250], [36, 1, 54, 250], [26, 1, 64, 250], [26, 1, 74, 250], [36, 1, 74, 251], [80, 1, 84, 251], [90, 1, 94, 251], [90, 1, 104, 251], [80, 1, 104, 250], [56, 1, 104, 250], [36, 1, 114, 250], [26, 1, 124, 250], [26, 1, 134, 250], [36, 1, 134, 251], [70, 1, 144, 251], [90, 1, 164, 4], [0, 195, 250, 86], [1, 154, 250, 56], [1, 164, 250, 36], [1, 174, 52, 1], [240, 30, 194, 251], [10, 1, 204, 251], [20, 1, 214, 251], [20, 1, 224, 251], [10, 1, 224, 250], [216, 1, 224, 250], [166, 1, 224, 250], [116, 1, 224, 250], [76, 1, 224, 250], [67, 1, 244, 250], [67, 1, 254, 250], [76, 1, 244, 4], [0, 35, 251, 20], [80, 1, 209, 20], [1, 184, 251, 30], [1, 164, 251, 40], [1, 154, 251, 70], [76, 1, 187, 144], [251, 100, 1, 114], [251, 110, 1, 74], [251, 120, 80, 1], [49, 80, 1, 14], [4, 0, 1, 80], [1, 167, 0, 230], [251, 30, 0, 200], [251, 20, 0, 170], [48, 2, 51, 170], [251, 0, 52, 2], [0, 48, 2, 17], [216, 52, 2, 2], [8, 0, 0, 56], [2, 0, 4, 0], [241, 8, 96, 0], [160, 250, 106, 0], [170, 250, 76, 0], [160, 250, 46, 0], [180, 250, 46, 0], [200, 250, 46, 0], [240, 40, 2, 17], [26, 36, 2, 81], [14, 249, 252, 1], [44, 32, 2, 113], [242, 1, 124, 249], [242, 1, 144, 4], [0, 0, 36, 2], [17, 16, 244, 0], [81, 184, 250, 46], [1, 224, 32, 2], [19, 36, 40, 2], [145, 56, 1, 244], [250, 86, 1, 254], [250, 106, 48, 2], [17, 244, 48, 2], [49, 166, 1, 234], [0, 1, 113, 176], [0, 240, 250, 176], [0, 200, 168, 1], [243, 2, 176, 0], [170, 250, 186, 0], [170, 250, 196, 0], [180, 250, 206, 1], [214, 250, 206, 40], [1, 112, 226, 1], [214, 250, 236, 0], [200, 200, 1, 1], [4, 0, 113, 246], [0, 180, 251, 10], [1, 174, 84, 1], [241, 16, 10, 1], [214, 251, 0, 1], [204, 251, 0, 1], [174, 251, 20, 1], [144, 251, 40, 1], [124, 251, 40, 1], [84, 251, 40, 1], [34, 251, 40, 1], [24, 4, 0, 241], [52, 50, 1, 34], [251, 70, 1, 64], [251, 70, 1, 114], [251, 70, 1, 134], [251, 71, 1, 134], [251, 51, 1, 134], [251, 11, 1, 134], [250, 217, 1, 134], [250, 177, 1, 134], [250, 147, 1, 124], [250, 147, 1, 154], [250, 147, 1, 204], [250, 147, 1, 214], [250, 146, 0, 190], [250, 146, 0, 180], [250, 146, 0, 170], [250, 136, 0, 170], [76, 2, 113, 116], [1, 194, 250, 116], [1, 214, 180, 1], [211, 106, 1, 224], [250, 96, 1, 214], [250, 86, 0, 190], [250, 86, 112, 2], [0, 124, 2, 17], [56, 36, 3, 241], [4, 214, 250, 36], [1, 214, 250, 66], [1, 214, 250, 76], [1, 194, 250, 76], [1, 164, 250, 56], [40, 2, 83, 124], [250, 26, 1, 104], [92, 2, 241, 34], [34, 250, 26, 1], [24, 250, 27, 1], [44, 250, 237, 1], [54, 251, 21, 1], [54, 251, 61, 1], [64, 251, 101, 1], [64, 251, 131, 1], [64, 251, 171, 1], [64, 251, 180, 1], [94, 251, 200, 1], [114, 251, 210, 1], [124, 251, 210, 1], [134, 4, 0, 241], [255, 143, 220, 1], [134, 251, 240, 1], [134, 252, 14, 1], [134, 252, 54, 1], [134, 252, 94, 1], [144, 252, 114, 1], [164, 252, 124, 1], [194, 252, 134, 1], [214, 252, 124, 1], [214, 252, 134, 1], [224, 252, 134, 1], [234, 252, 134, 2], [8, 252, 134, 2], [48, 252, 134, 2], [88, 252, 144, 2], [118, 252, 134, 2], [138, 252, 124, 2], [148, 252, 104, 2], [168, 252, 104, 2], [198, 252, 104, 2], [238, 252, 104, 3], [22, 252, 104, 3], [62, 252, 114, 3], [102, 252, 114, 3], [92, 252, 114, 3], [112, 252, 134, 3], [132, 252, 144, 3], [162, 252, 134, 3], [162, 252, 124, 3], [182, 252, 134, 3], [192, 252, 124, 4], [196, 252, 114, 4], [196, 252, 124, 4], [206, 252, 134, 4], [206, 253, 108, 4], [196, 254, 52, 4], [176, 254, 62, 4], [166, 254, 82, 4], [176, 254, 102, 4], [186, 254, 122, 4], [186, 254, 132, 4], [206, 254, 162, 4], [226, 254, 192, 4], [236, 254, 232, 5], [0, 255, 6, 5], [10, 255, 46, 5], [30, 255, 76, 5], [30, 255, 96, 5], [30, 255, 126, 5], [30, 255, 146, 5], [10, 255, 176, 5], [10, 255, 206, 5], [10, 255, 246, 5], [30, 0, 0, 5], [30, 0, 10, 5], [30, 0, 20, 5], [20, 0, 30, 5], [10, 0, 40, 5], [0, 0, 60, 4], [246, 0, 90, 5], [0, 0, 110, 4], [246, 0, 100, 4], [246, 0, 110, 4], [236, 0, 120, 4], [226, 0, 120, 4], [186, 0, 120, 4], [166, 0, 120, 4], [156, 0, 120, 4], [166, 0, 110, 4], [166, 0, 90, 4], [156, 0, 60, 4], [156, 0, 40, 4], [146, 0, 10, 4], [136, 255, 246, 4], [126, 255, 246, 4], [136, 255, 236, 4], [156, 255, 206, 4], [166, 255, 176, 4], [156, 255, 146, 4], [136, 255, 116, 4], [136, 255, 106, 4], [136, 255, 76, 4], [136, 255, 46, 4], [116, 255, 26, 4], [96, 255, 6, 4], [66, 254, 252, 4], [36, 255, 6, 4], [26, 255, 6, 3], [242, 254, 252, 3], [212, 254, 252, 3], [172, 254, 252, 3], [132, 254, 252, 3], [112, 254, 252, 3], [102, 254, 242, 3], [102, 254, 252, 3], [102, 254, 232, 3], [102, 254, 222, 3], [102, 254, 212, 3], [92, 254, 202, 3], [112, 254, 232, 3], [122, 254, 242, 3], [112, 254, 212, 3], [102, 254, 202, 3], [92, 254, 192, 24], [0, 0, 12, 0], [0, 20, 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253, 228, 3], [12, 180, 5, 0], [188, 5, 53, 248], [3, 2, 12, 0], [2, 192, 5, 17], [208, 192, 5, 21], [218, 196, 5, 21], [148, 196, 5, 18], [248, 192, 5, 35], [253, 238, 12, 0], [210, 228, 2, 98], [253, 218, 2, 68], [253, 218, 2, 48], [253, 228, 180, 3], [129, 254, 12, 2], [8, 254, 22, 1], [244, 244, 3, 2], [192, 5, 4, 188], [5, 2, 16, 5], [4, 188, 5, 177], [182, 1, 124, 254], [212, 1, 134, 254], [232, 1, 134, 180], [5, 113, 252, 0], [220, 254, 252, 0], [180, 164, 5, 83], [252, 0, 150, 254], [242, 172, 5, 241], [6, 228, 0, 160], [253, 118, 0, 160], [253, 18, 0, 170], [253, 8, 0, 160], [252, 254, 0, 170], [252, 244, 180, 5], [0, 176, 5, 240], [6, 170, 251, 230], [0, 180, 251, 230], [0, 210, 251, 220], [0, 230, 251, 220], [0, 240, 251, 220], [1, 14, 52, 5], [3, 180, 5, 81], [54, 251, 170, 1], [94, 176, 5, 241], [6, 170, 1, 144], [251, 170, 1, 144], [252, 94, 1, 154], [252, 114, 1, 174], [252, 134, 1, 194], [252, 144, 188, 8], [179, 234, 252, 144], [2, 8, 252, 144], [2, 48, 252, 144], 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40, 255, 136], [0, 40, 255, 86], [0, 40, 255, 36], [0, 40, 254, 242], [0, 40, 254, 192], [0, 40, 254, 132], [0, 40, 254, 82], [0, 40, 254, 32], [0, 40, 253, 238], [0, 40, 253, 178], [0, 40, 253, 128], [0, 40, 253, 78], [0, 40, 253, 48], [0, 40, 253, 38], [0, 50, 253, 58], [0, 70, 253, 98], [0, 70, 253, 148], [0, 70, 253, 198], [0, 70, 253, 248], [0, 70, 254, 42], [0, 70, 254, 102], [0, 70, 254, 152], [0, 70, 254, 202], [0, 70, 254, 252], [0, 70, 255, 56], [0, 70, 255, 106], [0, 70, 255, 156], [0, 70, 255, 176], [0, 70, 255, 186], [4, 0, 2, 40], [14, 0, 244, 13], [241, 6, 86, 0], [100, 255, 36, 0], [100, 254, 242, 0], [100, 254, 182, 0], [100, 254, 132, 0], [100, 254, 82, 208], [11, 2, 140, 11], [0, 88, 11, 0], [20, 11, 241, 72], [78, 0, 100, 253], [68, 0, 101, 253], [58, 0, 101, 253], [78, 0, 91, 253], [88, 0, 81, 253], [98, 0, 41, 253], [108, 255, 247, 253], [118, 255, 207, 253], [118, 255, 177, 253], [128, 255, 137, 253], [138, 255, 97, 253], [148, 255, 67, 253], [158, 255, 27, 253], [168, 254, 243, 253], [178, 254, 203, 253], [188, 254, 173, 253], [198, 254, 133, 253], [218, 254, 103, 253], [228, 254, 73, 253], [228, 254, 53, 253], [238, 254, 42, 254], [2, 254, 42, 2], [0, 243, 36, 62], [254, 53, 254, 72], [254, 63, 254, 62], [254, 73, 254, 42], [254, 73, 254, 2], [254, 73, 253, 218], [254, 73, 253, 188], [254, 73, 253, 158], [254, 73, 253, 168], [254, 93, 253, 168], [254, 63, 253, 158], [254, 53, 253, 148], [254, 42, 253, 158], [254, 43, 12, 0], [241, 22, 73, 253], [138, 254, 83, 253], [98, 254, 93, 253], [58, 254, 103, 253], [28, 254, 103, 253], [18, 254, 83, 253], [8, 254, 53, 252], [254, 254, 13, 252], [244, 254, 3, 252], [254, 253, 229, 238], [9, 2, 124, 10], [16, 199, 132, 10], [33, 253, 8, 4], [0, 0, 188, 10], [241, 255, 71, 239], [253, 8, 254, 23], [253, 18, 254, 53], [253, 38, 254, 73], [253, 48, 254, 103], [253, 78, 254, 123], [253, 98, 254, 143], [253, 118, 254, 173], [253, 128, 254, 193], [253, 148, 254, 213], [253, 168, 254, 233], [253, 188, 255, 7], [253, 208, 255, 27], [253, 228, 255, 47], [253, 238, 255, 77], [254, 2, 255, 97], [254, 22, 255, 117], [254, 52, 255, 137], [254, 82, 255, 147], [254, 102, 255, 157], [254, 132, 255, 167], [254, 162, 255, 177], [254, 192, 255, 187], [254, 212, 255, 197], [254, 242, 255, 207], [255, 16, 255, 217], [255, 46, 255, 227], [255, 66, 255, 237], [255, 96, 255, 247], [255, 126, 0, 1], [255, 156, 0, 11], [255, 176, 0, 21], [255, 206, 0, 31], [255, 226, 0, 31], [0, 0, 0, 31], [255, 246, 0, 21], [255, 216, 0, 21], [255, 246, 0, 31], [0, 30, 0, 41], [0, 50, 0, 21], [0, 70, 0, 21], [0, 80, 0, 21], [0, 90, 255, 247], [0, 90, 255, 237], [0, 100, 255, 247], [0, 120, 0, 21], [0, 140, 0, 51], [0, 160, 0, 81], [0, 180, 0, 101], [0, 190, 0, 131], [0, 210, 0, 151], [0, 210, 0, 181], [0, 220, 0, 211], [0, 210, 0, 241], [0, 220, 1, 15], [0, 210, 1, 45], [0, 210, 1, 75], [0, 210, 1, 105], [0, 210, 1, 135], [0, 210, 1, 165], [0, 220, 1, 195], [0, 220, 1, 225], [0, 220, 1, 255], [0, 230, 2, 19], [0, 230, 2, 49], [0, 240, 2, 79], [0, 240, 2, 109], [0, 250, 2, 139], [0, 250, 2, 169], [0, 250, 2, 199], [1, 4, 2, 229], [1, 4, 3, 3], [1, 4, 3, 33], [1, 14, 3, 63], [1, 14, 3, 83], [1, 14, 3, 113], [1, 24, 3, 143], [1, 24, 3, 173], [1, 24, 3, 203], [1, 34, 3, 233], [1, 34, 3, 253], [1, 34, 4, 7], [1, 34, 3, 253], [1, 34, 4, 7], [1, 44, 4, 7], [1, 44, 3, 253], [24, 0, 19, 44], [24, 0, 8, 16], [0, 241, 20, 44], [4, 17, 1, 54], [4, 17, 1, 74], [4, 17, 1, 84], [4, 17, 1, 104], [4, 17, 1, 114], [4, 17, 1, 124], [4, 17, 1, 134], [4, 17, 1, 144], [4, 7, 204, 63], [240, 0, 164, 4], [7, 1, 174, 4], [7, 1, 204, 4], [17, 1, 174, 4], [7]] ```
reef-actor commented 6 months ago

I have made progress on decoding the path. The SL60D is using LZ4 compression for the payload

The basic idea is to change decode_path_v1 to this:

def decode_path_v1(pathdata):
    header_length = BYTE_HEADER_LENGHT_PATH_V1 // 2
    data_arr = _hexStringToNumber(pathdata)

    isLz4 = True
    if(isLz4):
        encode_data_array = _hexStringToNumber(pathdata[BYTE_HEADER_LENGHT_PATH_V1:])
        max_buffer_length = 4336
        decode_data_array = LZ4_decompress(encode_data_array, max_buffer_length)

        path_data_arr = [decode_data_array[i:i + 4] for i in range(0, len(decode_data_array), 4)]
    else:
        path_data_arr = [data_arr[i:i + 4] for i in range(header_length, len(data_arr), 4)]

isLz4 and max_buffer_length should both be determined from the header, but I don't think we are currently parsing the header so I have just hardcoded the values (I copied the max_buffer_length value seen when running the same data through the Tuya Panel Demo code).

The x/y offsets are not quite right. To get the image above I had to x + 1800 and y - 3175. Also the len(point) == 4 check I mentioned earlier is not needed.

stream74 commented 4 months ago

I have made progress on decoding the path. The SL60D is using LZ4 compression for the payload

The basic idea is to change decode_path_v1 to this:

def decode_path_v1(pathdata):
    header_length = BYTE_HEADER_LENGHT_PATH_V1 // 2
    data_arr = _hexStringToNumber(pathdata)

    isLz4 = True
    if(isLz4):
        encode_data_array = _hexStringToNumber(pathdata[BYTE_HEADER_LENGHT_PATH_V1:])
        max_buffer_length = 4336
        decode_data_array = LZ4_decompress(encode_data_array, max_buffer_length)

        path_data_arr = [decode_data_array[i:i + 4] for i in range(0, len(decode_data_array), 4)]
    else:
        path_data_arr = [data_arr[i:i + 4] for i in range(header_length, len(data_arr), 4)]

isLz4 and max_buffer_length should both be determined from the header, but I don't think we are currently parsing the header so I have just hardcoded the values (I copied the max_buffer_length value seen when running the same data through the Tuya Panel Demo code).

The x/y offsets are not quite right. To get the image above I had to x + 1800 and y - 3175. Also the len(point) == 4 check I mentioned earlier is not needed.

How did you get the path on the map to work?You say to use isLz4, but how do I add it to Home Assistant?

reef-actor commented 4 months ago

I have made a pull request (Add support for compressed path data #43). If you are comfortable pulling in those changes you can get it working now, otherwise we need to wait for @oven-lab to merge the changes into this integration.

Francesco68 commented 3 weeks ago

Buon pomeriggio anche io sto combattendo con questa card, di seguito vi elenco cosa viene fuori nei logs:

Questo errore ha avuto origine da un'integrazione personalizzata.

Registratore: custom_components.tuya_cloud_map_extractor.config_flow Fonte: custom_components/tuya_cloud_map_extractor/config_flow.py:57 Integrazione: Tuya Cloud Map Extractor (documentazione, problemi) Prima occorrenza: 15:54:19 (1 occorrenze) Ultima registrazione: 15:54:19

not enough values to unpack (expected 2, got 1) Traceback (most recent call last): File "/usr/local/lib/python3.12/site-packages/requests/models.py", line 974, in json return complexjson.loads(self.text, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/usr/local/lib/python3.12/site-packages/simplejson/init.py", line 514, in loads return _default_decoder.decode(s) ^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/usr/local/lib/python3.12/site-packages/simplejson/decoder.py", line 386, in decode obj, end = self.raw_decode(s) ^^^^^^^^^^^^^^^^^^ File "/usr/local/lib/python3.12/site-packages/simplejson/decoder.py", line 416, in raw_decode return self.scan_once(s, idx=_w(s, idx).end()) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ simplejson.errors.JSONDecodeError: Expecting value: line 1 column 1 (char 0)

During handling of the above exception, another exception occurred:

Traceback (most recent call last): File "/config/custom_components/tuya_cloud_map_extractor/tuya_vacuum_map_extractor/main.py", line 47, in parse_path data = response.json() ^^^^^^^^^^^^^^^ File "/usr/local/lib/python3.12/site-packages/requests/models.py", line 978, in json raise RequestsJSONDecodeError(e.msg, e.doc, e.pos) requests.exceptions.JSONDecodeError: Expecting value: line 1 column 1 (char 0)

During handling of the above exception, another exception occurred:

Traceback (most recent call last): File "/config/custom_components/tuya_cloud_map_extractor/config_flow.py", line 57, in async_step_user headers, image = await validate(self.hass, user_input) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/config/custom_components/tuya_cloud_map_extractor/config_flow.py", line 214, in validate return await hass.async_add_executor_job( ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/usr/local/lib/python3.12/concurrent/futures/thread.py", line 58, in run result = self.fn(*self.args, **self.kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/config/custom_components/tuya_cloud_map_extractor/tuya_vacuum_map_extractor/main.py", line 192, in get_map raise e File "/config/custom_components/tuya_cloud_map_extractor/tuya_vacuum_map_extractor/main.py", line 189, in get_map path = parse_path(response, scale=scale, header=header) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/config/custom_components/tuya_cloud_map_extractor/tuya_vacuum_map_extractor/main.py", line 51, in parse_path path_data = decode_path_v1(data) ^^^^^^^^^^^^^^^^^^^^ File "/config/custom_components/tuya_cloud_map_extractor/tuya_vacuum_map_extractor/v1.py", line 111, in decode_path_v1 x, y = [_deal_pl(_highLowToInt(high, low)) for high, low in _partition(point, 2)] ^^^^ ValueError: not enough values to unpack (expected 2, got 1)