License_Classification / frontPrompt.py
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Update frontPrompt.py
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import numpy as np
import torch
import torchvision.transforms as T
from decord import VideoReader, cpu
from PIL import Image
from torchvision.transforms.functional import InterpolationMode
from transformers import AutoModel, AutoTokenizer
IMAGENET_MEAN = (0.485, 0.456, 0.406)
IMAGENET_STD = (0.229, 0.224, 0.225)
def build_transform(input_size):
MEAN, STD = IMAGENET_MEAN, IMAGENET_STD
transform = T.Compose([
T.Lambda(lambda img: img.convert('RGB') if img.mode != 'RGB' else img),
T.Resize((input_size, input_size), interpolation=InterpolationMode.BICUBIC),
T.ToTensor(),
T.Normalize(mean=MEAN, std=STD)
])
return transform
def preprocess_for_model(image):
"""Prepares an image for the OpenGVLab model."""
# Define the necessary image transformations
transform = T.Compose([
T.ToTensor(), # Convert to PyTorch Tensor
T.Normalize(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225]) # Normalize
])
image = transform(image).unsqueeze(0) # Add batch dimension
return image
def load_image(image_file):
transform = build_transform(input_size=800)
pixel_values = preprocess_for_model(image_file)
return pixel_values
def main(image_path,model,tokenizer):
pixel_values = load_image(image_path).to(torch.float32).to("cpu")
generation_config = dict(max_new_tokens=1024, do_sample=True)
question = """<image>\n**Instruction:**
Analyze the image to extract values for the specified keys. Use the detailed descriptions below to determine the correct value for each key. Handle missing or ambiguous data as instructed.
---
### Keys and Descriptions
1. **`surat_tanda_nomor_kendaraan_bermotor`**
- **Extract**: The value of the field labeled as "Surat Tanda Nomor Kendaraan Bermotor" and this is titel.
- **If the Field is Absent**: `"null"`
- **If the Field is Present but No Value is Provided**: `"empty"`
2. **`tempat_tanggal`**
- **Extract**: The location and date from the top right corner of the document.
- **Note**: This field does not have a title such as "Tempat - Tanggal."
- **Format**: `"CITY, DD MMM YYYY"` (e.g., `"JAKARTA, 07 DES 2018"`).
- **If the Field is Absent**: `"null"`
- **If the Field is Present but No Value is Provided**: `"empty"`
3. **`no`**
- **Extract**: The value in the "NO" field.
- **If the Field is Absent**: `"null"`
- **If the Field is Present but No Value is Provided**: `"empty"`
4. **`nomor_registrasi`**
- **Extract**: The "NOMOR REGISTRASI" field.
- **If the Field is Absent**: `"null"`
- **If the Field is Present but No Value is Provided**: `"empty"`
5. **`nama_pemilik`**
- **Extract**: The "NAMA PEMILIK" field.
- **If the Field is Absent**: `"null"`
- **If the Field is Present but No Value is Provided**: `"empty"`
6. **`alamat`**
- **Extract**: The "ALAMAT" field.
- **If the Field is Absent**: `"null"`
- **If the Field is Present but No Value is Provided**: `"empty"`
7. **`merk`**
- **Extract**: The "MERK" field.
- **If the Field is Absent**: `"null"`
- **If the Field is Present but No Value is Provided**: `"empty"`
8. **`type`**
- **Extract**: The "TYPE" field.
- **If the Field is Absent**: `"null"`
- **If the Field is Present but No Value is Provided**: `"empty"`
9. **`jenis`**
- **Extract**: The "JENIS" field.
- **If the Field is Absent**: `"null"`
- **If the Field is Present but No Value is Provided**: `"empty"`
10. **`model`**
- **Extract**: The "MODEL" field.
- **If the Field is Absent**: `"null"`
- **If the Field is Present but No Value is Provided**: `"empty"`
11. **`tahun_pembuatan`**
- **Extract**: The "TAHUN PEMBUATAN" field.
- **If the Field is Absent**: `"null"`
- **If the Field is Present but No Value is Provided**: `"empty"`
12. **`isi_silinder_daya_listrik`**
- **Extract**: The "ISI SILINDER / DAYA LISTRIK" field.
- **If the Field is Absent**: `"null"`
- **If the Field is Present but No Value is Provided**: `"empty"`
13. **`nomor_rangka`**
- **Extract**: The "NOMOR RANGKA" field.
- **If the Field is Absent**: `"null"`
- **If the Field is Present but No Value is Provided**: `"empty"`
14. **`nomor_mesin`**
- **Extract**: The "NOMOR MESIN" field.
- **If the Field is Absent**: `"null"`
- **If the Field is Present but No Value is Provided**: `"empty"`
15. **`nik_tdp_nie_kitas_kitap`**
- **Extract**: The "NIK/TDP/NIE/KITAS/KITAP" field.
- **If the Field is Absent**: `"null"`
- **If the Field is Present but No Value is Provided**: `"empty"`
16. **`warna`**
- **Extract**: The "WARNA" field.
- **If the Field is Absent**: `"null"`
- **If the Field is Present but No Value is Provided**: `"empty"`
17. **`bahan_bakar`**
- **Extract**: The "BAHAN BAKAR" field.
- **If the Field is Absent**: `"null"`
- **If the Field is Present but No Value is Provided**: `"empty"`
18. **`warna_tnkb`**
- **Extract**: The "WARNA TNKB" field.
- **If the Field is Absent**: `"null"`
- **If the Field is Present but No Value is Provided**: `"empty"`
19. **`tahun_registrasi`**
- **Extract**: The "TAHUN REGISTRASI" field.
- **If the Field is Absent**: `"null"`
- **If the Field is Present but No Value is Provided**: `"empty"`
20. **`nomor_bpkb`**
- **Extract**: The "NOMOR BPKB" field.
- **If the Field is Absent**: `"null"`
- **If the Field is Present but No Value is Provided**: `"empty"`
21. **`kode_lokasi`**
- **Extract**: The "KODE LOKASI" field.
- **If the Field is Absent**: `"null"`
- **If the Field is Present but No Value is Provided**: `"empty"`
22. **`no_urut_pendaftaran`**
- **Extract**: The "NO URUT PENDAFTARAN" field.
- **If the Field is Absent**: `"null"`
- **If the Field is Present but No Value is Provided**: `"empty"`
23. **`berlaku_sampai`**
- **Extract**: The "BERLAKU SAMPAI" field.
- **If the Field is Absent**: `"null"`
- **If the Field is Present but No Value is Provided**: `"empty"`
24. **`qr_code`**
- **Extract**: The value encoded in the QR code, if present.
- **If No QR Code is Found**: `"null"`
- **If a QR Code is Present but Contains No Data**: `"empty"`
---
### Output Format
```json
{
"surat_tanda_nomor_kendaraan_bermotor": "<value> OR empty OR null",
"tempat_tanggal": "<value> OR empty OR null",
"no": "<value> OR empty OR null",
"nomor_registrasi": "<value> OR empty OR null",
"nama_pemilik": "<value> OR empty OR null",
"alamat": "<value> OR empty OR null",
"merk": "<value> OR empty OR null",
"type": "<value> OR empty OR null",
"jenis": "<value> OR empty OR null",
"model": "<value> OR empty OR null",
"tahun_pembuatan": "<value> OR empty OR null",
"isi_silinder_daya_listrik": "<value> OR empty OR null",
"nomor_rangka": "<value> OR empty OR null",
"nomor_mesin": "<value> OR empty OR null",
"nik_tdp_nie_kitas_kitap": "<value> OR empty OR null",
"warna": "<value> OR empty OR null",
"bahan_bakar": "<value> OR empty OR null",
"warna_tnkb": "<value> OR empty OR null",
"tahun_registrasi": "<value> OR empty OR null",
"nomor_bpkb": "<value> OR empty OR null",
"kode_lokasi": "<value> OR empty OR null",
"no_urut_pendaftaran": "<value> OR empty OR null",
"berlaku_sampai": "<value> OR empty OR null"
"qr_code" : "<value> OR empty OR null"
}
### Reasoning Process
For each key, explain your reasoning:
Indicate whether the field was present.
Justify the extracted value or the use of "null" or "empty" as per the conditions.
Return Output:
Generate a JSON object:
{
"reasoning": "reasoning for each key",
"output JSON": "key-value pairs"
}
---
"""
print("Before requesting model................................................................................")
response = model.chat(tokenizer, pixel_values, question, generation_config)
print("After requesting model................................................................................",response)
return (f'User: {question}\nAssistant: {response}')