Hugging Face's logo

JustFadjrin
/
batik-vit-model-classification

Image Classification
Transformers
Safetensors
vit
vision-transformer
batik
indonesia
Model card Files
xet
 Community
JustFadjrin commited on
Commit
6927a5b
·
verified ·
1 Parent(s): 822453c

Upload folder using huggingface_hub

Browse files
Files changed (10) hide show
  1. .gitattributes +1 -0
  2. README.md +55 -0
  3. classification_report.txt +26 -0
  4. config.json +70 -0
  5. confusion_matrix.png +3 -0
  6. labels.json +68 -0
  7. model.safetensors +3 -0
  8. model_info.json +37 -0
  9. preprocessor_config.json +23 -0
  10. training_args.bin +3 -0
.gitattributes CHANGED
@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
33
  *.zip filter=lfs diff=lfs merge=lfs -text
34
  *.zst filter=lfs diff=lfs merge=lfs -text
35
  *tfevents* filter=lfs diff=lfs merge=lfs -text
 
 
33
  *.zip filter=lfs diff=lfs merge=lfs -text
34
  *.zst filter=lfs diff=lfs merge=lfs -text
35
  *tfevents* filter=lfs diff=lfs merge=lfs -text
36
+ confusion_matrix.png filter=lfs diff=lfs merge=lfs -text
README.md ADDED
@@ -0,0 +1,55 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ license: cc0-1.0
3
+ library_name: transformers
4
+ pipeline_tag: image-classification
5
+ tags:
6
+ - image-classification
7
+ - vision-transformer
8
+ - vit
9
+ - batik
10
+ - indonesia
11
+ ---
12
+
13
+ # Batik ViT Model Confident
14
+
15
+ Model ini adalah model klasifikasi jenis batik berbasis Vision Transformer (ViT).
16
+
17
+ Model digunakan pada project **Batik ViT Classifier** untuk mengklasifikasikan gambar batik Indonesia.
18
+
19
+ ## Dataset
20
+
21
+ Dataset berasal dari Kaggle:
22
+
23
+ **Batik Nusantara (Batik Indonesia) Dataset**
24
+ Author: HendryHB
25
+ Link: https://www.kaggle.com/datasets/hendryhb/batik-nusantara-batik-indonesia-dataset
26
+
27
+ ## Jenis Batik yang Dapat Dideteksi
28
+
29
+ Model ini dilatih untuk mengenali 20 jenis batik:
30
+
31
+ 1. Aceh Pintu Aceh
32
+ 2. Bali Barong
33
+ 3. Bali Merak
34
+ 4. DKI Ondel Ondel
35
+ 5. Jawa Barat Megamendung
36
+ 6. Jawa Timur Pring
37
+ 7. Kalimantan Dayak
38
+ 8. Lampung Gajah
39
+ 9. Madura Mataketeran
40
+ 10. Maluku Pala
41
+ 11. NTB Lumbung
42
+ 12. Papua Asmat
43
+ 13. Papua Cendrawasih
44
+ 14. Papua Tifa
45
+ 15. Solo Parang
46
+ 16. Sulawesi Selatan Lontara
47
+ 17. Sumatera Barat Rumah Minang
48
+ 18. Sumatera Utara Boraspati
49
+ 19. Yogyakarta Kawung
50
+ 20. Yogyakarta Parang
51
+
52
+ ## Catatan
53
+
54
+ Model ini tidak 100% akurat karena dataset masih terbatas dan jenis batik di Indonesia sangat banyak.
55
+ Hasil prediksi dipengaruhi oleh kualitas gambar, pencahayaan, sudut pengambilan foto, background, dan kemiripan motif antar kelas.
classification_report.txt ADDED
@@ -0,0 +1,26 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ precision recall f1-score support
2
+
3
+ Aceh_Pintu_Aceh 1.0000 0.7500 0.8571 8
4
+ Bali_Barong 0.8889 1.0000 0.9412 8
5
+ Bali_Merak 0.8889 1.0000 0.9412 8
6
+ DKI_Ondel_Ondel 1.0000 1.0000 1.0000 8
7
+ JawaBarat_Megamendung 1.0000 1.0000 1.0000 8
8
+ JawaTimur_Pring 1.0000 1.0000 1.0000 8
9
+ Kalimantan_Dayak 1.0000 1.0000 1.0000 8
10
+ Lampung_Gajah 0.8750 0.8750 0.8750 8
11
+ Madura_Mataketeran 1.0000 1.0000 1.0000 8
12
+ Maluku_Pala 1.0000 1.0000 1.0000 8
13
+ NTB_Lumbung 0.8000 1.0000 0.8889 8
14
+ Papua_Asmat 1.0000 1.0000 1.0000 8
15
+ Papua_Cendrawasih 1.0000 0.8750 0.9333 8
16
+ Papua_Tifa 1.0000 0.8750 0.9333 8
17
+ Solo_Parang 0.5000 0.3750 0.4286 8
18
+ SulawesiSelatan_Lontara 1.0000 1.0000 1.0000 8
19
+ SumateraBarat_Rumah_Minang 0.8750 0.8750 0.8750 8
20
+ SumateraUtara_Boraspati 1.0000 1.0000 1.0000 8
21
+ Yogyakarta_Kawung 1.0000 1.0000 1.0000 8
22
+ Yogyakarta_Parang 0.5000 0.6250 0.5556 8
23
+
24
+ accuracy 0.9125 160
25
+ macro avg 0.9164 0.9125 0.9115 160
26
+ weighted avg 0.9164 0.9125 0.9115 160
config.json ADDED
@@ -0,0 +1,70 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "architectures": [
3
+ "ViTForImageClassification"
4
+ ],
5
+ "attention_probs_dropout_prob": 0.0,
6
+ "dtype": "float32",
7
+ "encoder_stride": 16,
8
+ "hidden_act": "gelu",
9
+ "hidden_dropout_prob": 0.0,
10
+ "hidden_size": 768,
11
+ "id2label": {
12
+ "0": "Aceh_Pintu_Aceh",
13
+ "1": "Bali_Barong",
14
+ "2": "Bali_Merak",
15
+ "3": "DKI_Ondel_Ondel",
16
+ "4": "JawaBarat_Megamendung",
17
+ "5": "JawaTimur_Pring",
18
+ "6": "Kalimantan_Dayak",
19
+ "7": "Lampung_Gajah",
20
+ "8": "Madura_Mataketeran",
21
+ "9": "Maluku_Pala",
22
+ "10": "NTB_Lumbung",
23
+ "11": "Papua_Asmat",
24
+ "12": "Papua_Cendrawasih",
25
+ "13": "Papua_Tifa",
26
+ "14": "Solo_Parang",
27
+ "15": "SulawesiSelatan_Lontara",
28
+ "16": "SumateraBarat_Rumah_Minang",
29
+ "17": "SumateraUtara_Boraspati",
30
+ "18": "Yogyakarta_Kawung",
31
+ "19": "Yogyakarta_Parang"
32
+ },
33
+ "image_size": 224,
34
+ "initializer_range": 0.02,
35
+ "intermediate_size": 3072,
36
+ "label2id": {
37
+ "Aceh_Pintu_Aceh": 0,
38
+ "Bali_Barong": 1,
39
+ "Bali_Merak": 2,
40
+ "DKI_Ondel_Ondel": 3,
41
+ "JawaBarat_Megamendung": 4,
42
+ "JawaTimur_Pring": 5,
43
+ "Kalimantan_Dayak": 6,
44
+ "Lampung_Gajah": 7,
45
+ "Madura_Mataketeran": 8,
46
+ "Maluku_Pala": 9,
47
+ "NTB_Lumbung": 10,
48
+ "Papua_Asmat": 11,
49
+ "Papua_Cendrawasih": 12,
50
+ "Papua_Tifa": 13,
51
+ "Solo_Parang": 14,
52
+ "SulawesiSelatan_Lontara": 15,
53
+ "SumateraBarat_Rumah_Minang": 16,
54
+ "SumateraUtara_Boraspati": 17,
55
+ "Yogyakarta_Kawung": 18,
56
+ "Yogyakarta_Parang": 19
57
+ },
58
+ "layer_norm_eps": 1e-12,
59
+ "model_type": "vit",
60
+ "num_attention_heads": 12,
61
+ "num_channels": 3,
62
+ "num_hidden_layers": 12,
63
+ "patch_size": 16,
64
+ "pooler_act": "tanh",
65
+ "pooler_output_size": 768,
66
+ "problem_type": "single_label_classification",
67
+ "qkv_bias": true,
68
+ "transformers_version": "5.0.0",
69
+ "use_cache": false
70
+ }
confusion_matrix.png ADDED

Git LFS Details

  • SHA256: 8f007b9666cbd0cebd86693253da9969e744b75424ce47f187a93e6064f5bc64
  • Pointer size: 131 Bytes
  • Size of remote file: 411 kB
labels.json ADDED
@@ -0,0 +1,68 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "class_names": [
3
+ "Aceh_Pintu_Aceh",
4
+ "Bali_Barong",
5
+ "Bali_Merak",
6
+ "DKI_Ondel_Ondel",
7
+ "JawaBarat_Megamendung",
8
+ "JawaTimur_Pring",
9
+ "Kalimantan_Dayak",
10
+ "Lampung_Gajah",
11
+ "Madura_Mataketeran",
12
+ "Maluku_Pala",
13
+ "NTB_Lumbung",
14
+ "Papua_Asmat",
15
+ "Papua_Cendrawasih",
16
+ "Papua_Tifa",
17
+ "Solo_Parang",
18
+ "SulawesiSelatan_Lontara",
19
+ "SumateraBarat_Rumah_Minang",
20
+ "SumateraUtara_Boraspati",
21
+ "Yogyakarta_Kawung",
22
+ "Yogyakarta_Parang"
23
+ ],
24
+ "label2id": {
25
+ "Aceh_Pintu_Aceh": 0,
26
+ "Bali_Barong": 1,
27
+ "Bali_Merak": 2,
28
+ "DKI_Ondel_Ondel": 3,
29
+ "JawaBarat_Megamendung": 4,
30
+ "JawaTimur_Pring": 5,
31
+ "Kalimantan_Dayak": 6,
32
+ "Lampung_Gajah": 7,
33
+ "Madura_Mataketeran": 8,
34
+ "Maluku_Pala": 9,
35
+ "NTB_Lumbung": 10,
36
+ "Papua_Asmat": 11,
37
+ "Papua_Cendrawasih": 12,
38
+ "Papua_Tifa": 13,
39
+ "Solo_Parang": 14,
40
+ "SulawesiSelatan_Lontara": 15,
41
+ "SumateraBarat_Rumah_Minang": 16,
42
+ "SumateraUtara_Boraspati": 17,
43
+ "Yogyakarta_Kawung": 18,
44
+ "Yogyakarta_Parang": 19
45
+ },
46
+ "id2label": {
47
+ "0": "Aceh_Pintu_Aceh",
48
+ "1": "Bali_Barong",
49
+ "2": "Bali_Merak",
50
+ "3": "DKI_Ondel_Ondel",
51
+ "4": "JawaBarat_Megamendung",
52
+ "5": "JawaTimur_Pring",
53
+ "6": "Kalimantan_Dayak",
54
+ "7": "Lampung_Gajah",
55
+ "8": "Madura_Mataketeran",
56
+ "9": "Maluku_Pala",
57
+ "10": "NTB_Lumbung",
58
+ "11": "Papua_Asmat",
59
+ "12": "Papua_Cendrawasih",
60
+ "13": "Papua_Tifa",
61
+ "14": "Solo_Parang",
62
+ "15": "SulawesiSelatan_Lontara",
63
+ "16": "SumateraBarat_Rumah_Minang",
64
+ "17": "SumateraUtara_Boraspati",
65
+ "18": "Yogyakarta_Kawung",
66
+ "19": "Yogyakarta_Parang"
67
+ }
68
+ }
model.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:c958e62f4f4a19dd4b9a5a0be7927443e2edc7404b6c35b1c2b769c17b10dbd0
3
+ size 343279344
model_info.json ADDED
@@ -0,0 +1,37 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "model_name": "google/vit-base-patch16-224-in21k",
3
+ "num_classes": 20,
4
+ "class_names": [
5
+ "Aceh_Pintu_Aceh",
6
+ "Bali_Barong",
7
+ "Bali_Merak",
8
+ "DKI_Ondel_Ondel",
9
+ "JawaBarat_Megamendung",
10
+ "JawaTimur_Pring",
11
+ "Kalimantan_Dayak",
12
+ "Lampung_Gajah",
13
+ "Madura_Mataketeran",
14
+ "Maluku_Pala",
15
+ "NTB_Lumbung",
16
+ "Papua_Asmat",
17
+ "Papua_Cendrawasih",
18
+ "Papua_Tifa",
19
+ "Solo_Parang",
20
+ "SulawesiSelatan_Lontara",
21
+ "SumateraBarat_Rumah_Minang",
22
+ "SumateraUtara_Boraspati",
23
+ "Yogyakarta_Kawung",
24
+ "Yogyakarta_Parang"
25
+ ],
26
+ "train_samples": 512,
27
+ "validation_samples": 128,
28
+ "test_samples": 160,
29
+ "test_accuracy": 0.9125,
30
+ "test_macro_f1": 0.9114589169000935,
31
+ "average_confidence_all": 0.7706013917922974,
32
+ "average_confidence_correct": 0.7880493402481079,
33
+ "average_margin_all": 0.728288471698761,
34
+ "recommended_threshold_high": 0.6,
35
+ "recommended_threshold_medium": 0.4,
36
+ "recommended_margin": 0.2
37
+ }
preprocessor_config.json ADDED
@@ -0,0 +1,23 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "do_convert_rgb": null,
3
+ "do_normalize": true,
4
+ "do_rescale": true,
5
+ "do_resize": true,
6
+ "image_mean": [
7
+ 0.5,
8
+ 0.5,
9
+ 0.5
10
+ ],
11
+ "image_processor_type": "ViTImageProcessor",
12
+ "image_std": [
13
+ 0.5,
14
+ 0.5,
15
+ 0.5
16
+ ],
17
+ "resample": 2,
18
+ "rescale_factor": 0.00392156862745098,
19
+ "size": {
20
+ "height": 224,
21
+ "width": 224
22
+ }
23
+ }
training_args.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:5014926af151076c390ca67959e1747b032f71d4ef5e752cd6fa481813f0f1db
3
+ size 5265