added

.gitattributes

@@ -33,3 +33,10 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+*.o filter=lfs diff=lfs merge=lfs -text
+*.so filter=lfs diff=lfs merge=lfs -text
+*.1 filter=lfs diff=lfs merge=lfs -text
+*.2 filter=lfs diff=lfs merge=lfs -text
+*.0 filter=lfs diff=lfs merge=lfs -text
+*.mp4 filter=lfs diff=lfs merge=lfs -text
+*.doubango filter=lfs diff=lfs merge=lfs -text

.gitignore

@@ -0,0 +1,3 @@
+.idea
+__pycache__/
+python/__pycache__/

app.py

@@ -0,0 +1,70 @@
+import os
+import subprocess
+import glob
+import gradio as gr
+from gradio.components import Gallery, Video, Textbox
+from classificatsion_video_demo import process
+
+
+def get_car_numbers(result_folder):
+    # change current working directory to binare/linux/mu   gdfg
+    current_dir = os.getcwd()
+    os.chdir("binaries/linux/x86_64")
+
+    # construct and run the command
+    # command = "python ../../../python/setup.py build_ext --inplace -v"
+    # process = subprocess.Popen(command, shell=True, stdin=subprocess.PIPE)
+    command = "PYTHONPATH=$PYTHONPATH:.:../../../python LD_LIBRARY_PATH=.:$LD_LIBRARY_PATH python ../../../scripts/alpr/license_plate_recognizer.py --image ../../../"+result_folder+" --assets ../../../assets"
+    process = subprocess.Popen(command, shell=True, stdin=subprocess.PIPE)
+
+    # send newline character to standard input
+    process.communicate(input='\n'.encode())
+
+    # wait for the subprocess to exit
+    process.wait()
+    os.chdir(current_dir)
+    return 0
+
+def predict(video_path):
+    """
+    Gradio interface orqali yuklab olingan videodan problem framelarni ajratib olinadi va resultat sifatida Galleryga chiqariladi
+    :param video_path:
+    :return: file
+    """
+    # Your image processing code here
+    # print(video_path)
+    _path = "assets/result_imgs"
+    images = glob.glob(f'{_path}/*.jpg')
+    for image in images:
+        os.remove(image)
+    problem, good, result = process(video_path)
+    images = glob.glob(f'{_path}/*.jpg')
+
+    get_car_numbers(result)
+    # # selected_images = [images[0],images[len(images)//2],images[-1]]
+    return problem+good, problem, good,images
+    # return 0, 0, 0, images
+    
+
+my_example = [
+    # ['video/vid_39_1284-2_1202.mp4']
+    # ['video/vid_39_1284-2_1174.mp4']
+]
+
+my_title = "Video Klassifikatsiya"
+my_description = "128-4 qoida `To’xtash chizig’ini bosish` bo'yicha video analiz"
+all_frame = Textbox(label="Umumiy framelar soni")
+problem_frame = Textbox(label="Muammoli framelar soni")
+good_frame = Textbox(label="Muammosiz framelar soni")
+
+problem_frames = Gallery(label="Muammoli rasmlar", elem_id="gallery").style(
+    grid=[3], height="auto"
+)
+input_video = Video(label="Kiruvchi video") # Create input video component
+
+gr.Interface(fn=predict,
+             inputs=input_video,
+             outputs=[all_frame,problem_frame,good_frame,problem_frames],
+             title=my_title,
+             examples=my_example,
+             description=my_description).launch()

assets/README.md

@@ -0,0 +1,9 @@
+- [fonts](fonts): Fonts used to display the license plates. You don't need these files in your application.
+- [images](images): Sample images. You don't need these files in your application.
+- [models](models): Tensorflow models. Not all files in this folder are required. Check [models/README.md](models/README.md).
+- [models.amlogic_npu](models.amlogic_npu): [Amlogic NPU](https://www.amlogic.com/) models. Not all files in this folder are required. Check [models.amlogic_npu/README.md](models.amlogic_npu/README.md).
+- [models.openvino](models.openvino): [Intel OpenVINO](https://docs.openvinotoolkit.org/latest/index.html) models. Not all files in this folder are required. Check [models.openvino/README.md](models.openvino/README.md).
+- [models.tensorrt](models.tensorrt): [NVIDIA TensorRT](https://developer.nvidia.com/tensorrt) models. Not all files in this folder are required. Check [models.tensorrt/README.md](models.tensorrt/README.md).
+
+
+

assets/fonts/GlNummernschildEng-XgWd-license.txt

@@ -0,0 +1,8 @@
+https://www.wfonts.com/font/gl-nummernschild-eng
+
+GL-Nummernschild-EngmediumCLP-GL-Nummernschild-EngGL-Nummernschild-EngVersion 20110112 GL-Nummernschild-EngGutenberg Labo
+http://gutenberg.sourceforge.jp/These fonts are free softwares.
+
+Unlimited permission is granted to use, copy, and distribute it, with or without modification, either commercially and noncommercially.
+
+THESE FONTS ARE PROVIDED ''AS IS'' WITHOUT WARRANTY.

assets/models.amlogic_npu/PID0x88/ultimateALPR-SDK_detect_main.mobile.model.amlogic.doubango

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+size 8408484

assets/models.amlogic_npu/PID0x88/ultimateALPR-SDK_detect_pysearch.mobile.model.amlogic.doubango

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assets/models.amlogic_npu/PID0x88/ultimateALPR-SDK_klass_lpci.mobile.model.amlogic.doubango

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assets/models.amlogic_npu/PID0x88/ultimateALPR-SDK_klass_vbsr.mobile.model.amlogic.doubango

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assets/models.amlogic_npu/PID0x88/ultimateALPR-SDK_klass_vcr.mobile.model.amlogic.doubango

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assets/models.amlogic_npu/PID0x88/ultimateALPR-SDK_klass_vmmr.mobile.model.amlogic.doubango

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+version https://git-lfs.github.com/spec/v1
+oid sha256:27183f6b7344d5803919c5942397be43f91f1ceb4cf7086b3ab4be81ed547206
+size 10934206

assets/models.amlogic_npu/README.md

@@ -0,0 +1,51 @@
+
+- [Files](#files)
+  - [supported_hardware.txt](#files-supported_hardware)
+  - [pid_serial_mapping.txt](#pid_serial_mapping)
+- [Models-requirement](#models-requirement)
+
+<hr />
+
+Not all files in this folder are required. It depends on the [features](https://www.doubango.org/SDKs/anpr/docs/Features.html) you want to activate.
+
+**This entire folder is useless if your hardware isn't Amlogic or you've disabled NPU ([Neural Processing Unit](https://en.wikichip.org/wiki/neural_processor)) acceleration.**
+
+<a name="files"></a>
+# Files
+
+<a name="files-supported_hardware"></a>
+## supported_hardware.txt
+[This file](supported_hardware.txt) contains the list of hardware names (case insensitive) for which NPU ([Neural Processing Unit](https://en.wikichip.org/wiki/neural_processor)) acceleration will be enabled. Your hardware must be listed in this file. 
+You can edit this file to include your hardware name. To get the name of your hardware: `cat /proc/cpuinfo | grep Hardware`.
+
+<a name="pid_serial_mapping"></a>
+## pid_serial_mapping.txt
+[This file](pid_serial_mapping.txt) contains the mapping between the PID of the models and the 4-first digits of your serial number. More at [Model Transcoding and Running User Guide (1.0).pdf](https://github.com/khadas/aml_npu_sdk/blob/master/docs/en/Model%20Transcoding%20and%20Running%20User%20Guide%20(1.0).pdf) page 9.
+
+| PID | serial (4-first digits) |
+|-------- | --- |
+|0x7D|290a|
+|**0x88**|**290b**|
+|0x99|2b0a|
+|0xA1|300a|
+|0xA1|300b|
+|0x99|2f0a|
+|0xB9|2f0b|
+|0xBE|330a|
+|0xBE|330b|
+|0xE8|380a|
+|0xE8|380b|
+
+When I run `cat /proc/cpuinfo | grep Serial` on my Khadas VIM3 I get `Serial          : 290b100001111500001731343258****`, that means my 4-first digits are `290b` which means my PID is `0x88` which means my models will be inside [PID0x88](PID0x88) folder.
+Please contact us via the [dev-group](https://groups.google.com/g/doubango-ai) if the folder correspoding to your PID is empty.
+
+<a name="models-requirement"></a>
+# Models requirement
+| Folder | Requirement |
+|-------- | --- |
+| ultimateALPR-SDK_detect_main.mobile.model.amlogic.doubango | **Always required when NPU acceleration is enabled** |
+| ultimateALPR-SDK_detect_pysearch.mobile.model.amlogic.doubango | **Always required when NPU acceleration is enabled** |
+| ultimateALPR-SDK_klass_lpci.mobile.model.amlogic.doubango | Only if NPU acceleration is enabled and you want [License Plate Country Identification (LPCI)](https://www.doubango.org/SDKs/anpr/docs/Features.html#license-plate-country-identification-lpci) |
+| ultimateALPR-SDK_klass_vbsr.mobile.model.amlogic.doubango | Only if NPU acceleration is enabled and you want [Vehicle Color Recognition (VCR)](https://www.doubango.org/SDKs/anpr/docs/Features.html#vehicle-color-recognition-vcr) |
+| ultimateALPR-SDK_klass_vcr.mobile.model.amlogic.doubango | Only if NPU acceleration is enabled and you want [Vehicle Make Model Recognition (VMMR)](https://www.doubango.org/SDKs/anpr/docs/Features.html#vehicle-make-model-recognition-vmmr) |
+| ultimateALPR-SDK_klass_vmmr.mobile.model.amlogic.doubango | Only if NPU acceleration is enabled and you want [Vehicle Body Style Recognition (VBSR)](https://www.doubango.org/SDKs/anpr/docs/Features.html#vehicle-body-style-recognition-vbsr) |

assets/models.amlogic_npu/pid_serial_mapping.txt

@@ -0,0 +1,11 @@
+0x7D,290a
+0x88,290b
+0x99,2b0a
+0xA1,300a
+0xA1,300b
+0x99,2f0a
+0xB9,2f0b
+0xBE,330a
+0xBE,330b
+0xE8,380a
+0xE8,380b

assets/models.amlogic_npu/supported_hardware.txt

@@ -0,0 +1,2 @@
+Amlogic
+Khadas VIM3

assets/models/README.md

@@ -0,0 +1,50 @@
+- Not all files in this folder are required. It depends on your CPU type.
+
+- All models listed here (**.model.doubango**) are useless on NVIDIA Jetson (ARM). The models for the NVIDIA Jetson devices are under [models.tensorrt](../models.tensorrt).
+
+# All charsets #
+
+|  | ARM | x86 |comment
+|-------- | --- | --- | ---|
+| ultimateALPR-SDK_detect_main.desktop.model.doubango | No | **Yes** | **Always required** |
+| ultimateALPR-SDK_detect_pysearch.desktop.model.doubango | No | **Yes** | **Always required** |
+| ultimateALPR-SDK_detecti_main.mobile.model.doubango | **Yes** | No | **Always required** |
+| ultimateALPR-SDK_detecti_pysearch.mobile.model.doubango | **Yes** | No | **Always required** |
+| ultimateALPR-SDK_klass_labels_lpci.txt.doubango | **Yes** | **Yes** | Only if you want [License Plate Country Identification (LPCI)](https://www.doubango.org/SDKs/anpr/docs/Features.html#license-plate-country-identification-lpci) |
+| ultimateALPR-SDK_klass_lpci.desktop.model.doubango | No | **Yes** | Only if you want [License Plate Country Identification (LPCI)](https://www.doubango.org/SDKs/anpr/docs/Features.html#license-plate-country-identification-lpci) |
+| ultimateALPR-SDK_klassi_lpci.mobile.model.doubango | **Yes** | No | Only if you want [License Plate Country Identification (LPCI)](https://www.doubango.org/SDKs/anpr/docs/Features.html#license-plate-country-identification-lpci) |
+| ultimateALPR-SDK_klass_labels_vcr.txt.doubango | **Yes** | **Yes** | Only if you want [Vehicle Color Recognition (VCR)](https://www.doubango.org/SDKs/anpr/docs/Features.html#vehicle-color-recognition-vcr) |
+| ultimateALPR-SDK_klass_vcr.desktop.model.doubango | No | **Yes** | Only if you want [Vehicle Color Recognition (VCR)](https://www.doubango.org/SDKs/anpr/docs/Features.html#vehicle-color-recognition-vcr) |
+| ultimateALPR-SDK_klassi_vcr.mobile.model.doubango | **Yes** | No | Only if you want [Vehicle Color Recognition (VCR)](https://www.doubango.org/SDKs/anpr/docs/Features.html#vehicle-color-recognition-vcr) |
+| ultimateALPR-SDK_klass_labels_vmmr.txt.doubango | **Yes** | **Yes** | Only if you want [Vehicle Make Model Recognition (VMMR)](https://www.doubango.org/SDKs/anpr/docs/Features.html#vehicle-make-model-recognition-vmmr) |
+| ultimateALPR-SDK_klass_vmmr.desktop.model.doubango | No | **Yes** | Only if you want [Vehicle Make Model Recognition (VMMR)](https://www.doubango.org/SDKs/anpr/docs/Features.html#vehicle-make-model-recognition-vmmr) |
+| ultimateALPR-SDK_klassi_vmmr.mobile.model.doubango | **Yes** | No | Only if you want [Vehicle Make Model Recognition (VMMR)](https://www.doubango.org/SDKs/anpr/docs/Features.html#vehicle-make-model-recognition-vmmr) |
+| ultimateALPR-SDK_klass_labels_vbsr.txt.doubango | **Yes** | **Yes** | Only if you want [Vehicle Body Style Recognition (VBSR)](https://www.doubango.org/SDKs/anpr/docs/Features.html#vehicle-body-style-recognition-vbsr) |
+| ultimateALPR-SDK_klass_vbsr.desktop.model.doubango | No | **Yes** | Only if you want [Vehicle Body Style Recognition (VBSR)](https://www.doubango.org/SDKs/anpr/docs/Features.html#vehicle-body-style-recognition-vbsr) |
+| ultimateALPR-SDK_klassi_vbsr.mobile.model.doubango | **Yes** | No | Only if you want [Vehicle Body Style Recognition (VBSR)](https://www.doubango.org/SDKs/anpr/docs/Features.html#vehicle-body-style-recognition-vbsr) |
+
+
+# Latin ([A-Z0-9]) charsets #
+
+|  | ARM | x86 |
+|-------- | --- | --- |
+| charset_anpr_latin_size=37.txt | **Yes** | **Yes** |
+| ultimateALPR-SDK_recogn2x150_latin.desktop.model.doubango | No | **Yes** |
+| ultimateALPR-SDK_recogn1x100_latin.desktop.model.doubango | **Yes** | No |
+
+# Korean charsets #
+
+|  | ARM | x86 |
+|-------- | --- | --- |
+| charset_anpr_korean_size=78.txt | **Yes** | **Yes** |
+| ultimateALPR-SDK_recogn2x150_korean.desktop.model.doubango | No | **Yes** |
+| ultimateALPR-SDK_recogn1x100_korean.desktop.model.doubango | **Yes** | No |
+
+# Chinese charsets #
+
+|  | ARM | x86 |
+|-------- | --- | --- |
+| charset_anpr_chinese_size=73.txt | **Yes** | **Yes** |
+| ultimateALPR-SDK_recogn2x150_chinese.desktop.model.doubango | No | **Yes** |
+| ultimateALPR-SDK_recogn1x100_chinese.desktop.model.doubango | **Yes** | No |
+

assets/models/charset_anpr_chinese_size=73.txt

@@ -0,0 +1,73 @@
+0	<nul>
+1	0
+2	1
+3	2
+4	3
+5	4
+6	5
+7	6
+8	7
+9	8
+10	9
+11	A
+12	B
+13	C
+14	D
+15	E
+16	F
+17	G
+18	H
+19	I
+20	J
+21	K
+22	L
+23	M
+24	N
+25	O
+26	P
+27	Q
+28	R
+29	S
+30	T
+31	U
+32	V
+33	W
+34	X
+35	Y
+36	Z
+37	云
+38	京
+39	冀
+40	吉
+41	学
+42	宁
+43	川
+44	挂
+45	新
+46	晋
+47	桂
+48	沪
+49	津
+50	浙
+51	渝
+52	港
+53	湘
+54	澳
+55	琼
+56	甘
+57	皖
+58	粤
+59	苏
+60	蒙
+61	藏
+62	警
+63	豫
+64	贵
+65	赣
+66	辽
+67	鄂
+68	闽
+69	陕
+70	青
+71	鲁
+72	黑

assets/models/charset_anpr_korean_size=78.txt

@@ -0,0 +1,78 @@
+0	<nul>
+1	0
+2	1
+3	2
+4	3
+5	4
+6	5
+7	6
+8	7
+9	8
+10	9
+11	가
+12	강
+13	거
+14	경
+15	고
+16	광
+17	교
+18	구
+19	기
+20	나
+21	남
+22	너
+23	노
+24	누
+25	다
+26	대
+27	더
+28	도
+29	두
+30	라
+31	러
+32	령
+33	로
+34	루
+35	리
+36	린
+37	마
+38	머
+39	모
+40	무
+41	므
+42	바
+43	배
+44	버
+45	보
+46	부
+47	북
+48	사
+49	산
+50	서
+51	세
+52	소
+53	수
+54	아
+55	어
+56	오
+57	외
+58	우
+59	울
+60	원
+61	육
+62	이
+63	인
+64	자
+65	저
+66	전
+67	제
+68	조
+69	종
+70	주
+71	천
+72	충
+73	타
+74	하
+75	허
+76	호
+77	후

assets/models/charset_anpr_latin_size=37.txt

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+0	<nul>
+1	A
+2	B
+3	C
+4	D
+5	E
+6	F
+7	G
+8	H
+9	I
+10	J
+11	K
+12	L
+13	M
+14	N
+15	O
+16	P
+17	Q
+18	R
+19	S
+20	T
+21	U
+22	V
+23	W
+24	X
+25	Y
+26	Z
+27	0
+28	1
+29	2
+30	3
+31	4
+32	5
+33	6
+34	7
+35	8
+36	9

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