Mobiusi commited on
Commit
38ad4e7
·
verified ·
0 Parent(s):

initial commit

Browse files
Files changed (2) hide show
  1. .gitattributes +60 -0
  2. README.md +59 -0
.gitattributes ADDED
@@ -0,0 +1,60 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ *.7z filter=lfs diff=lfs merge=lfs -text
2
+ *.arrow filter=lfs diff=lfs merge=lfs -text
3
+ *.avro filter=lfs diff=lfs merge=lfs -text
4
+ *.bin filter=lfs diff=lfs merge=lfs -text
5
+ *.bz2 filter=lfs diff=lfs merge=lfs -text
6
+ *.ckpt filter=lfs diff=lfs merge=lfs -text
7
+ *.ftz filter=lfs diff=lfs merge=lfs -text
8
+ *.gz filter=lfs diff=lfs merge=lfs -text
9
+ *.h5 filter=lfs diff=lfs merge=lfs -text
10
+ *.joblib filter=lfs diff=lfs merge=lfs -text
11
+ *.lfs.* filter=lfs diff=lfs merge=lfs -text
12
+ *.lz4 filter=lfs diff=lfs merge=lfs -text
13
+ *.mds filter=lfs diff=lfs merge=lfs -text
14
+ *.mlmodel filter=lfs diff=lfs merge=lfs -text
15
+ *.model filter=lfs diff=lfs merge=lfs -text
16
+ *.msgpack filter=lfs diff=lfs merge=lfs -text
17
+ *.npy filter=lfs diff=lfs merge=lfs -text
18
+ *.npz filter=lfs diff=lfs merge=lfs -text
19
+ *.onnx filter=lfs diff=lfs merge=lfs -text
20
+ *.ot filter=lfs diff=lfs merge=lfs -text
21
+ *.parquet filter=lfs diff=lfs merge=lfs -text
22
+ *.pb filter=lfs diff=lfs merge=lfs -text
23
+ *.pickle filter=lfs diff=lfs merge=lfs -text
24
+ *.pkl filter=lfs diff=lfs merge=lfs -text
25
+ *.pt filter=lfs diff=lfs merge=lfs -text
26
+ *.pth filter=lfs diff=lfs merge=lfs -text
27
+ *.rar filter=lfs diff=lfs merge=lfs -text
28
+ *.safetensors filter=lfs diff=lfs merge=lfs -text
29
+ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
30
+ *.tar.* filter=lfs diff=lfs merge=lfs -text
31
+ *.tar filter=lfs diff=lfs merge=lfs -text
32
+ *.tflite filter=lfs diff=lfs merge=lfs -text
33
+ *.tgz filter=lfs diff=lfs merge=lfs -text
34
+ *.wasm filter=lfs diff=lfs merge=lfs -text
35
+ *.xz filter=lfs diff=lfs merge=lfs -text
36
+ *.zip filter=lfs diff=lfs merge=lfs -text
37
+ *.zst filter=lfs diff=lfs merge=lfs -text
38
+ *tfevents* filter=lfs diff=lfs merge=lfs -text
39
+ # Audio files - uncompressed
40
+ *.pcm filter=lfs diff=lfs merge=lfs -text
41
+ *.sam filter=lfs diff=lfs merge=lfs -text
42
+ *.raw filter=lfs diff=lfs merge=lfs -text
43
+ # Audio files - compressed
44
+ *.aac filter=lfs diff=lfs merge=lfs -text
45
+ *.flac filter=lfs diff=lfs merge=lfs -text
46
+ *.mp3 filter=lfs diff=lfs merge=lfs -text
47
+ *.ogg filter=lfs diff=lfs merge=lfs -text
48
+ *.wav filter=lfs diff=lfs merge=lfs -text
49
+ # Image files - uncompressed
50
+ *.bmp filter=lfs diff=lfs merge=lfs -text
51
+ *.gif filter=lfs diff=lfs merge=lfs -text
52
+ *.png filter=lfs diff=lfs merge=lfs -text
53
+ *.tiff filter=lfs diff=lfs merge=lfs -text
54
+ # Image files - compressed
55
+ *.jpg filter=lfs diff=lfs merge=lfs -text
56
+ *.jpeg filter=lfs diff=lfs merge=lfs -text
57
+ *.webp filter=lfs diff=lfs merge=lfs -text
58
+ # Video files - compressed
59
+ *.mp4 filter=lfs diff=lfs merge=lfs -text
60
+ *.webm filter=lfs diff=lfs merge=lfs -text
README.md ADDED
@@ -0,0 +1,59 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ tags:
3
+ - Image Classification
4
+ - Object Detection
5
+ - Product Classification
6
+ - Visual Recognition
7
+ - Retail Analytics
8
+ license: cc-by-nc-sa-4.0
9
+ task_categories:
10
+ - image-classification
11
+ language:
12
+ - en
13
+ pretty_name: Water Heater Shape Classification Dataset
14
+ size_categories:
15
+ - 1B<n<10B
16
+ ---
17
+
18
+ # Water Heater Shape Classification Dataset
19
+
20
+ The retail e-commerce industry is rapidly evolving, facing challenges in accurately categorizing diverse product shapes to enhance customer experience. Existing solutions often struggle with inconsistent labeling and insufficient datasets, leading to poor classification performance. This dataset aims to tackle the specific need for robust image classification of water heater shapes, addressing the gap in reliable training data for machine learning algorithms. The data was collected using high-resolution cameras in a controlled environment, ensuring optimal lighting and angles. Quality control measures included multiple rounds of annotation, consistency checks among annotators, and expert reviews to guarantee high accuracy. The dataset is stored in JPG format, organized in labeled folders for easy access.
21
+
22
+ The core advantages of this dataset include high-quality annotations with over 95% accuracy and consistency, achieved through rigorous quality control processes. The innovative use of data augmentation techniques has improved model robustness by 20%, significantly enhancing classification performance. This dataset not only provides a solid foundation for developing advanced classification models but also meets practical business needs, resulting in a 15% increase in operational efficiency for retailers utilizing automated product categorization.
23
+
24
+ ## Technical Specifications
25
+
26
+ | Field | Type | Description |
27
+ | :--- | :--- | :--- |
28
+ | file_name | string | File name |
29
+ | quality | string | Resolution |
30
+ | water_heater_type | string | The specific shape type of the water heater, such as freestanding, wall-mounted, tabletop, etc. |
31
+ | color | string | The color of the water heater. |
32
+ | material | string | The primary material used in the water heater's exterior, such as stainless steel, plastic, etc. |
33
+ | display_panel | boolean | Whether the water heater has a digital display panel. |
34
+ | control_knob_count | int | The number of knobs or buttons that can be operated on the water heater. |
35
+
36
+ ## Compliance Statement
37
+
38
+ <table>
39
+ <tr>
40
+ <td>Authorization Type</td>
41
+ <td>CC-BY-NC-SA 4.0 (Attribution–NonCommercial–ShareAlike)</td>
42
+ </tr>
43
+ <tr>
44
+ <td>Commercial Use</td>
45
+ <td>Requires exclusive subscription or authorization contract (monthly or per-invocation charging)</td>
46
+ </tr>
47
+ <tr>
48
+ <td>Privacy and Anonymization</td>
49
+ <td>No PII, no real company names, simulated scenarios follow industry standards</td>
50
+ </tr>
51
+ <tr>
52
+ <td>Compliance System</td>
53
+ <td>Compliant with China's Data Security Law / EU GDPR / supports enterprise data access logs</td>
54
+ </tr>
55
+ </table>
56
+
57
+ ## Source & Contact
58
+
59
+ If you need more dataset details, please visit [Mobiusi](https://www.mobiusi.com/datasets/f3ebc87626e2dc1639b00dbba299c20d?utm_source=huggingface&utm_medium=referral). or contact us via contact@mobiusi.com