stuff

.gitattributes

@@ -33,3 +33,4 @@ 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
+*.caffemodel filter=lfs diff=lfs merge=lfs -text

.gitattributes copy

@@ -0,0 +1,36 @@
+*.7z filter=lfs diff=lfs merge=lfs -text
+*.arrow filter=lfs diff=lfs merge=lfs -text
+*.bin filter=lfs diff=lfs merge=lfs -text
+*.bz2 filter=lfs diff=lfs merge=lfs -text
+*.ckpt filter=lfs diff=lfs merge=lfs -text
+*.ftz filter=lfs diff=lfs merge=lfs -text
+*.gz filter=lfs diff=lfs merge=lfs -text
+*.h5 filter=lfs diff=lfs merge=lfs -text
+*.joblib filter=lfs diff=lfs merge=lfs -text
+*.lfs.* filter=lfs diff=lfs merge=lfs -text
+*.mlmodel filter=lfs diff=lfs merge=lfs -text
+*.model filter=lfs diff=lfs merge=lfs -text
+*.msgpack filter=lfs diff=lfs merge=lfs -text
+*.npy filter=lfs diff=lfs merge=lfs -text
+*.npz filter=lfs diff=lfs merge=lfs -text
+*.onnx filter=lfs diff=lfs merge=lfs -text
+*.ot filter=lfs diff=lfs merge=lfs -text
+*.parquet filter=lfs diff=lfs merge=lfs -text
+*.pb filter=lfs diff=lfs merge=lfs -text
+*.pickle filter=lfs diff=lfs merge=lfs -text
+*.pkl filter=lfs diff=lfs merge=lfs -text
+*.pt filter=lfs diff=lfs merge=lfs -text
+*.pth filter=lfs diff=lfs merge=lfs -text
+*.rar filter=lfs diff=lfs merge=lfs -text
+*.safetensors filter=lfs diff=lfs merge=lfs -text
+saved_model/**/* filter=lfs diff=lfs merge=lfs -text
+*.tar.* filter=lfs diff=lfs merge=lfs -text
+*.tar filter=lfs diff=lfs merge=lfs -text
+*.tflite filter=lfs diff=lfs merge=lfs -text
+*.tgz filter=lfs diff=lfs merge=lfs -text
+*.wasm filter=lfs diff=lfs merge=lfs -text
+*.xz 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
+*.caffemodel filter=lfs diff=lfs merge=lfs -text

.gitignore

@@ -0,0 +1 @@
+**/__pycache__/**

Dockerfile

@@ -0,0 +1,18 @@
+FROM python:3.11
+
+WORKDIR /code
+
+COPY ./requirements.txt /code/requirements.txt
+
+RUN pip install --no-cache-dir --upgrade -r /code/requirements.txt
+
+RUN useradd -m -u 1000 user
+USER user
+ENV HOME=/home/user \
+    PATH=/home/user/.local/bin:$PATH
+
+WORKDIR $HOME/app
+
+COPY --chown=user . $HOME/app
+
+CMD ["python", "manage.py", "runserver", "0.0.0.0:7860"]

README copy.md

@@ -0,0 +1,11 @@
+---
+title: OpenCvColourize
+emoji: 📚
+colorFrom: red
+colorTo: pink
+sdk: docker
+pinned: false
+license: mit
+---
+
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

colourize/asgi.py

@@ -0,0 +1,16 @@
+"""
+ASGI config for colourize project.
+
+It exposes the ASGI callable as a module-level variable named ``application``.
+
+For more information on this file, see
+https://docs.djangoproject.com/en/5.0/howto/deployment/asgi/
+"""
+
+import os
+
+from django.core.asgi import get_asgi_application
+
+os.environ.setdefault('DJANGO_SETTINGS_MODULE', 'colourize.settings')
+
+application = get_asgi_application()

colourize/settings.py

@@ -0,0 +1,128 @@
+"""
+Django settings for colourize project.
+
+Generated by 'django-admin startproject' using Django 5.0.3.
+
+For more information on this file, see
+https://docs.djangoproject.com/en/5.0/topics/settings/
+
+For the full list of settings and their values, see
+https://docs.djangoproject.com/en/5.0/ref/settings/
+"""
+
+from pathlib import Path
+
+# Build paths inside the project like this: BASE_DIR / 'subdir'.
+BASE_DIR = Path(__file__).resolve().parent.parent
+
+
+# Quick-start development settings - unsuitable for production
+# See https://docs.djangoproject.com/en/5.0/howto/deployment/checklist/
+
+# SECURITY WARNING: keep the secret key used in production secret!
+SECRET_KEY = 'django-insecure-5^=_be4pw&9qxni5p!!2zd77#vo*5af1^5ppo)@nbt07of2lua'
+
+# SECURITY WARNING: don't run with debug turned on in production!
+DEBUG = True
+
+ALLOWED_HOSTS = []
+
+CORS_ALLOW_ALL_ORIGINS = True
+
+# Application definition
+
+INSTALLED_APPS = [
+    'django.contrib.admin',
+    'django.contrib.auth',
+    'django.contrib.contenttypes',
+    'django.contrib.sessions',
+    'django.contrib.messages',
+    'django.contrib.staticfiles',
+    'imageModel.apps.ImagemodelConfig',
+    'corsheaders',
+    'rest_framework',
+]
+
+MIDDLEWARE = [
+    'django.middleware.security.SecurityMiddleware',
+    'django.contrib.sessions.middleware.SessionMiddleware',
+    'corsheaders.middleware.CorsMiddleware',
+    'django.middleware.common.CommonMiddleware',
+    'django.middleware.csrf.CsrfViewMiddleware',
+    'django.contrib.auth.middleware.AuthenticationMiddleware',
+    'django.contrib.messages.middleware.MessageMiddleware',
+    'django.middleware.clickjacking.XFrameOptionsMiddleware',
+]
+
+ROOT_URLCONF = 'colourize.urls'
+
+TEMPLATES = [
+    {
+        'BACKEND': 'django.template.backends.django.DjangoTemplates',
+        'DIRS': [],
+        'APP_DIRS': True,
+        'OPTIONS': {
+            'context_processors': [
+                'django.template.context_processors.debug',
+                'django.template.context_processors.request',
+                'django.contrib.auth.context_processors.auth',
+                'django.contrib.messages.context_processors.messages',
+            ],
+        },
+    },
+]
+
+WSGI_APPLICATION = 'colourize.wsgi.application'
+
+
+# Database
+# https://docs.djangoproject.com/en/5.0/ref/settings/#databases
+
+DATABASES = {
+    'default': {
+        'ENGINE': 'django.db.backends.sqlite3',
+        'NAME': BASE_DIR / 'db.sqlite3',
+    }
+}
+
+
+# Password validation
+# https://docs.djangoproject.com/en/5.0/ref/settings/#auth-password-validators
+
+AUTH_PASSWORD_VALIDATORS = [
+    {
+        'NAME': 'django.contrib.auth.password_validation.UserAttributeSimilarityValidator',
+    },
+    {
+        'NAME': 'django.contrib.auth.password_validation.MinimumLengthValidator',
+    },
+    {
+        'NAME': 'django.contrib.auth.password_validation.CommonPasswordValidator',
+    },
+    {
+        'NAME': 'django.contrib.auth.password_validation.NumericPasswordValidator',
+    },
+]
+
+
+# Internationalization
+# https://docs.djangoproject.com/en/5.0/topics/i18n/
+
+LANGUAGE_CODE = 'en-us'
+
+TIME_ZONE = 'UTC'
+
+USE_I18N = True
+
+USE_TZ = True
+
+
+# Static files (CSS, JavaScript, Images)
+# https://docs.djangoproject.com/en/5.0/howto/static-files/
+
+STATIC_URL = 'static/'
+
+# Default primary key field type
+# https://docs.djangoproject.com/en/5.0/ref/settings/#default-auto-field
+
+DEFAULT_AUTO_FIELD = 'django.db.models.BigAutoField'

colourize/urls.py

@@ -0,0 +1,23 @@
+"""
+URL configuration for colourize project.
+
+The `urlpatterns` list routes URLs to views. For more information please see:
+    https://docs.djangoproject.com/en/5.0/topics/http/urls/
+Examples:
+Function views
+    1. Add an import:  from my_app import views
+    2. Add a URL to urlpatterns:  path('', views.home, name='home')
+Class-based views
+    1. Add an import:  from other_app.views import Home
+    2. Add a URL to urlpatterns:  path('', Home.as_view(), name='home')
+Including another URLconf
+    1. Import the include() function: from django.urls import include, path
+    2. Add a URL to urlpatterns:  path('blog/', include('blog.urls'))
+"""
+from django.contrib import admin
+from django.urls import path, include
+
+urlpatterns = [
+    path('admin/', admin.site.urls),
+    path('api/', include('imageModel.urls', namespace='imageModel')),
+]

colourize/wsgi.py

@@ -0,0 +1,16 @@
+"""
+WSGI config for colourize project.
+
+It exposes the WSGI callable as a module-level variable named ``application``.
+
+For more information on this file, see
+https://docs.djangoproject.com/en/5.0/howto/deployment/wsgi/
+"""
+
+import os
+
+from django.core.wsgi import get_wsgi_application
+
+os.environ.setdefault('DJANGO_SETTINGS_MODULE', 'colourize.settings')
+
+application = get_wsgi_application()

imageModel/admin.py

@@ -0,0 +1,3 @@
+from django.contrib import admin
+
+# Register your models here.

imageModel/apps.py

@@ -0,0 +1,6 @@
+from django.apps import AppConfig
+
+
+class ImagemodelConfig(AppConfig):
+    default_auto_field = 'django.db.models.BigAutoField'
+    name = 'imageModel'

imageModel/models.py

@@ -0,0 +1,3 @@
+from django.db import models
+
+# Create your models here.

imageModel/tests.py

@@ -0,0 +1,3 @@
+from django.test import TestCase
+
+# Create your tests here.

imageModel/urls.py

@@ -0,0 +1,7 @@
+from django.urls import path
+from .views import ImageModelView
+
+app_name='imageModel'
+urlpatterns = [
+    path('colourize/', ImageModelView.as_view()),
+]

imageModel/utils/main.py

@@ -0,0 +1,60 @@
+import numpy as np
+import cv2
+import os
+
+DIR = r"C:/Users/dilji/OneDrive/Documents/CodingFiles/codeInit/backend/imageModel/utils"
+PROTOTEXT = os.path.join(DIR, r"models/colorization_deploy_v2.prototxt")
+MODEL = os.path.join(DIR, r"models/colorization_release_v2.caffemodel")
+POINTS = os.path.join(DIR, r"models/pts_in_hull.npy")
+
+def colorize(image_path):
+    image_path = os.path.join(DIR, image_path)
+    print("[INFO] Loading model...")
+    net = cv2.dnn.readNetFromCaffe(prototxt=PROTOTEXT, caffeModel=MODEL)
+    pts = np.load(POINTS)
+    
+    class8 = net.getLayerId("class8_ab")
+    conv8 = net.getLayerId("conv8_313_rh")
+    pts = pts.transpose().reshape(2, 313, 1, 1)
+    net.getLayer(class8).blobs = [pts.astype("float32")]
+    net.getLayer(conv8).blobs = [np.full([1, 313], 2.606, dtype="float32")]
+    
+    print("[INFO] Loading image...")
+    image = cv2.imread(image_path)
+    scaled = image.astype("float32") / 255.0
+    lab = cv2.cvtColor(scaled, cv2.COLOR_BGR2LAB)
+    
+    resized = cv2.resize(lab, (224, 224))
+    L = cv2.split(resized)[0]
+    L -= 50
+    
+    print("[INFO] Colorizing image...")
+    net.setInput(cv2.dnn.blobFromImage(L))
+    ab = net.forward()[0, :, :, :].transpose((1, 2, 0))
+    ab = cv2.resize(ab, (image.shape[1], image.shape[0]))
+    L = cv2.split(lab)[0]
+    colorized = np.concatenate((L[:, :, np.newaxis], ab), axis=2)
+    colorized = cv2.cvtColor(colorized, cv2.COLOR_LAB2BGR)
+    colorized = np.clip(colorized, 0, 1)
+    
+    colorized = (255*colorized)
+    colorized = colorized.astype(np.uint8)
+    
+    cv2.imwrite(os.path.join(DIR, "colorized.jpg"), colorized)
+    return os.path.join(DIR, "colorized.jpg")
+
+
+def save_image(image_data, path):
+    with open(os.path.join(DIR,path), "wb") as f:
+        for chunk in image_data.chunks():
+            f.write(chunk)
+        f.close()
+    return path
+
+
+
+def cleanup():
+    if (os.path.exists(os.path.join(DIR, "input.jpg"))):
+        os.remove(os.path.join(DIR, "input.jpg"))
+    if (os.path.exists(os.path.join(DIR, "colorized.jpg"))):
+        os.remove(os.path.join(DIR, "colorized.jpg"))

imageModel/utils/models/colorization_deploy_v2.prototxt

@@ -0,0 +1,589 @@
+name: "LtoAB"
+
+layer {
+  name: "data_l"
+  type: "Input"
+  top: "data_l"
+  input_param {
+    shape { dim: 1 dim: 1 dim: 224 dim: 224 }
+  }
+}
+
+# *****************
+# ***** conv1 *****
+# *****************
+layer {
+  name: "bw_conv1_1"
+  type: "Convolution"
+  bottom: "data_l"
+  top: "conv1_1"
+  # param {lr_mult: 0 decay_mult: 0} 
+  # param {lr_mult: 0 decay_mult: 0} 
+  convolution_param {
+    num_output: 64
+    pad: 1
+    kernel_size: 3
+  }
+}
+layer {
+  name: "relu1_1"
+  type: "ReLU"
+  bottom: "conv1_1"
+  top: "conv1_1"
+}
+layer {
+  name: "conv1_2"
+  type: "Convolution"
+  bottom: "conv1_1"
+  top: "conv1_2"
+  # param {lr_mult: 0 decay_mult: 0} 
+  # param {lr_mult: 0 decay_mult: 0} 
+  convolution_param {
+    num_output: 64
+    pad: 1
+    kernel_size: 3
+    stride: 2
+  }
+}
+layer {
+  name: "relu1_2"
+  type: "ReLU"
+  bottom: "conv1_2"
+  top: "conv1_2"
+}
+layer {
+  name: "conv1_2norm"
+  type: "BatchNorm"
+  bottom: "conv1_2"
+  top: "conv1_2norm"
+  batch_norm_param{ }
+  param {lr_mult: 0 decay_mult: 0}
+  param {lr_mult: 0 decay_mult: 0}
+  param {lr_mult: 0 decay_mult: 0}
+}
+# *****************
+# ***** conv2 *****
+# *****************
+layer {
+  name: "conv2_1"
+  type: "Convolution"
+  # bottom: "conv1_2"
+  bottom: "conv1_2norm"
+  # bottom: "pool1"
+  top: "conv2_1"
+  # param {lr_mult: 0 decay_mult: 0} 
+  # param {lr_mult: 0 decay_mult: 0} 
+  convolution_param {
+    num_output: 128
+    pad: 1
+    kernel_size: 3
+  }
+}
+layer {
+  name: "relu2_1"
+  type: "ReLU"
+  bottom: "conv2_1"
+  top: "conv2_1"
+}
+layer {
+  name: "conv2_2"
+  type: "Convolution"
+  bottom: "conv2_1"
+  top: "conv2_2"
+  # param {lr_mult: 0 decay_mult: 0} 
+  # param {lr_mult: 0 decay_mult: 0} 
+  convolution_param {
+    num_output: 128
+    pad: 1
+    kernel_size: 3
+    stride: 2
+  }
+}
+layer {
+  name: "relu2_2"
+  type: "ReLU"
+  bottom: "conv2_2"
+  top: "conv2_2"
+}
+layer {
+  name: "conv2_2norm"
+  type: "BatchNorm"
+  bottom: "conv2_2"
+  top: "conv2_2norm"
+  batch_norm_param{ }
+  param {lr_mult: 0 decay_mult: 0}
+  param {lr_mult: 0 decay_mult: 0}
+  param {lr_mult: 0 decay_mult: 0}
+}
+# *****************
+# ***** conv3 *****
+# *****************
+layer {
+  name: "conv3_1"
+  type: "Convolution"
+  # bottom: "conv2_2"
+  bottom: "conv2_2norm"
+  # bottom: "pool2"
+  top: "conv3_1"
+  # param {lr_mult: 0 decay_mult: 0} 
+  # param {lr_mult: 0 decay_mult: 0} 
+  convolution_param {
+    num_output: 256
+    pad: 1
+    kernel_size: 3
+  }
+}
+layer {
+  name: "relu3_1"
+  type: "ReLU"
+  bottom: "conv3_1"
+  top: "conv3_1"
+}
+layer {
+  name: "conv3_2"
+  type: "Convolution"
+  bottom: "conv3_1"
+  top: "conv3_2"
+  # param {lr_mult: 0 decay_mult: 0} 
+  # param {lr_mult: 0 decay_mult: 0} 
+  convolution_param {
+    num_output: 256
+    pad: 1
+    kernel_size: 3
+  }
+}
+layer {
+  name: "relu3_2"
+  type: "ReLU"
+  bottom: "conv3_2"
+  top: "conv3_2"
+}
+layer {
+  name: "conv3_3"
+  type: "Convolution"
+  bottom: "conv3_2"
+  top: "conv3_3"
+  # param {lr_mult: 0 decay_mult: 0} 
+  # param {lr_mult: 0 decay_mult: 0} 
+  convolution_param {
+    num_output: 256
+    pad: 1
+    kernel_size: 3
+    stride: 2
+  }
+}
+layer {
+  name: "relu3_3"
+  type: "ReLU"
+  bottom: "conv3_3"
+  top: "conv3_3"
+}
+layer {
+  name: "conv3_3norm"
+  type: "BatchNorm"
+  bottom: "conv3_3"
+  top: "conv3_3norm"
+  batch_norm_param{ }
+  param {lr_mult: 0 decay_mult: 0}
+  param {lr_mult: 0 decay_mult: 0}
+  param {lr_mult: 0 decay_mult: 0}
+}
+# *****************
+# ***** conv4 *****
+# *****************
+layer {
+  name: "conv4_1"
+  type: "Convolution"
+  # bottom: "conv3_3"
+  bottom: "conv3_3norm"
+  # bottom: "pool3"
+  top: "conv4_1"
+  # param {lr_mult: 0 decay_mult: 0} 
+  # param {lr_mult: 0 decay_mult: 0} 
+  convolution_param {
+    num_output: 512
+    kernel_size: 3
+    stride: 1
+    pad: 1
+    dilation: 1
+  }
+}
+layer {
+  name: "relu4_1"
+  type: "ReLU"
+  bottom: "conv4_1"
+  top: "conv4_1"
+}
+layer {
+  name: "conv4_2"
+  type: "Convolution"
+  bottom: "conv4_1"
+  top: "conv4_2"
+  # param {lr_mult: 0 decay_mult: 0} 
+  # param {lr_mult: 0 decay_mult: 0} 
+  convolution_param {
+    num_output: 512
+    kernel_size: 3
+    stride: 1
+    pad: 1
+    dilation: 1
+  }
+}
+layer {
+  name: "relu4_2"
+  type: "ReLU"
+  bottom: "conv4_2"
+  top: "conv4_2"
+}
+layer {
+  name: "conv4_3"
+  type: "Convolution"
+  bottom: "conv4_2"
+  top: "conv4_3"
+  # param {lr_mult: 0 decay_mult: 0} 
+  # param {lr_mult: 0 decay_mult: 0} 
+  convolution_param {
+    num_output: 512
+    kernel_size: 3
+    stride: 1
+    pad: 1
+    dilation: 1
+  }
+}
+layer {
+  name: "relu4_3"
+  type: "ReLU"
+  bottom: "conv4_3"
+  top: "conv4_3"
+}
+layer {
+  name: "conv4_3norm"
+  type: "BatchNorm"
+  bottom: "conv4_3"
+  top: "conv4_3norm"
+  batch_norm_param{ }
+  param {lr_mult: 0 decay_mult: 0}
+  param {lr_mult: 0 decay_mult: 0}
+  param {lr_mult: 0 decay_mult: 0}
+}
+# *****************
+# ***** conv5 *****
+# *****************
+layer {
+  name: "conv5_1"
+  type: "Convolution"
+  # bottom: "conv4_3"
+  bottom: "conv4_3norm"
+  # bottom: "pool4"
+  top: "conv5_1"
+  # param {lr_mult: 0 decay_mult: 0} 
+  # param {lr_mult: 0 decay_mult: 0}   
+  convolution_param {
+    num_output: 512
+    kernel_size: 3
+    stride: 1
+    pad: 2
+    dilation: 2
+  }
+}
+layer {
+  name: "relu5_1"
+  type: "ReLU"
+  bottom: "conv5_1"
+  top: "conv5_1"
+}
+layer {
+  name: "conv5_2"
+  type: "Convolution"
+  bottom: "conv5_1"
+  top: "conv5_2"
+  # param {lr_mult: 0 decay_mult: 0} 
+  # param {lr_mult: 0 decay_mult: 0} 
+  convolution_param {
+    num_output: 512
+    kernel_size: 3
+    stride: 1
+    pad: 2
+    dilation: 2
+  }
+}
+layer {
+  name: "relu5_2"
+  type: "ReLU"
+  bottom: "conv5_2"
+  top: "conv5_2"
+}
+layer {
+  name: "conv5_3"
+  type: "Convolution"
+  bottom: "conv5_2"
+  top: "conv5_3"
+  # param {lr_mult: 0 decay_mult: 0} 
+  # param {lr_mult: 0 decay_mult: 0} 
+  convolution_param {
+    num_output: 512
+    kernel_size: 3
+    stride: 1
+    pad: 2
+    dilation: 2
+  }
+}
+layer {
+  name: "relu5_3"
+  type: "ReLU"
+  bottom: "conv5_3"
+  top: "conv5_3"
+}
+layer {
+  name: "conv5_3norm"
+  type: "BatchNorm"
+  bottom: "conv5_3"
+  top: "conv5_3norm"
+  batch_norm_param{ }
+  param {lr_mult: 0 decay_mult: 0}
+  param {lr_mult: 0 decay_mult: 0}
+  param {lr_mult: 0 decay_mult: 0}
+}
+# *****************
+# ***** conv6 *****
+# *****************
+layer {
+  name: "conv6_1"
+  type: "Convolution"
+  bottom: "conv5_3norm"
+  top: "conv6_1"
+  convolution_param {
+    num_output: 512
+    kernel_size: 3
+    pad: 2
+    dilation: 2
+  }
+}
+layer {
+  name: "relu6_1"
+  type: "ReLU"
+  bottom: "conv6_1"
+  top: "conv6_1"
+}
+layer {
+  name: "conv6_2"
+  type: "Convolution"
+  bottom: "conv6_1"
+  top: "conv6_2"
+  convolution_param {
+    num_output: 512
+    kernel_size: 3
+    pad: 2
+    dilation: 2
+  }
+}
+layer {
+  name: "relu6_2"
+  type: "ReLU"
+  bottom: "conv6_2"
+  top: "conv6_2"
+}
+layer {
+  name: "conv6_3"
+  type: "Convolution"
+  bottom: "conv6_2"
+  top: "conv6_3"
+  convolution_param {
+    num_output: 512
+    kernel_size: 3
+    pad: 2
+    dilation: 2
+  }
+}
+layer {
+  name: "relu6_3"
+  type: "ReLU"
+  bottom: "conv6_3"
+  top: "conv6_3"
+}
+layer {
+  name: "conv6_3norm"
+  type: "BatchNorm"
+  bottom: "conv6_3"
+  top: "conv6_3norm"
+  batch_norm_param{ }
+  param {lr_mult: 0 decay_mult: 0}
+  param {lr_mult: 0 decay_mult: 0}
+  param {lr_mult: 0 decay_mult: 0}
+}
+# *****************
+# ***** conv7 *****
+# *****************
+layer {
+  name: "conv7_1"
+  type: "Convolution"
+  bottom: "conv6_3norm"
+  top: "conv7_1"
+  convolution_param {
+    num_output: 512
+    kernel_size: 3
+    pad: 1
+    dilation: 1
+  }
+}
+layer {
+  name: "relu7_1"
+  type: "ReLU"
+  bottom: "conv7_1"
+  top: "conv7_1"
+}
+layer {
+  name: "conv7_2"
+  type: "Convolution"
+  bottom: "conv7_1"
+  top: "conv7_2"
+  convolution_param {
+    num_output: 512
+    kernel_size: 3
+    pad: 1
+    dilation: 1
+  }
+}
+layer {
+  name: "relu7_2"
+  type: "ReLU"
+  bottom: "conv7_2"
+  top: "conv7_2"
+}
+layer {
+  name: "conv7_3"
+  type: "Convolution"
+  bottom: "conv7_2"
+  top: "conv7_3"
+  convolution_param {
+    num_output: 512
+    kernel_size: 3
+    pad: 1
+    dilation: 1
+  }
+}
+layer {
+  name: "relu7_3"
+  type: "ReLU"
+  bottom: "conv7_3"
+  top: "conv7_3"
+}
+layer {
+  name: "conv7_3norm"
+  type: "BatchNorm"
+  bottom: "conv7_3"
+  top: "conv7_3norm"
+  batch_norm_param{ }
+  param {lr_mult: 0 decay_mult: 0}
+  param {lr_mult: 0 decay_mult: 0}
+  param {lr_mult: 0 decay_mult: 0}
+}
+# *****************
+# ***** conv8 *****
+# *****************
+layer {
+  name: "conv8_1"
+  type: "Deconvolution"
+  bottom: "conv7_3norm"
+  top: "conv8_1"
+  convolution_param {
+    num_output: 256
+    kernel_size: 4
+    pad: 1
+    dilation: 1
+    stride: 2
+  }
+}
+layer {
+  name: "relu8_1"
+  type: "ReLU"
+  bottom: "conv8_1"
+  top: "conv8_1"
+}
+layer {
+  name: "conv8_2"
+  type: "Convolution"
+  bottom: "conv8_1"
+  top: "conv8_2"
+  convolution_param {
+    num_output: 256
+    kernel_size: 3
+    pad: 1
+    dilation: 1
+  }
+}
+layer {
+  name: "relu8_2"
+  type: "ReLU"
+  bottom: "conv8_2"
+  top: "conv8_2"
+}
+layer {
+  name: "conv8_3"
+  type: "Convolution"
+  bottom: "conv8_2"
+  top: "conv8_3"
+  convolution_param {
+    num_output: 256
+    kernel_size: 3
+    pad: 1
+    dilation: 1
+  }
+}
+layer {
+  name: "relu8_3"
+  type: "ReLU"
+  bottom: "conv8_3"
+  top: "conv8_3"
+}
+# *******************
+# ***** Softmax *****
+# *******************
+layer {
+  name: "conv8_313"
+  type: "Convolution"
+  bottom: "conv8_3"
+  top: "conv8_313"
+  convolution_param {
+    num_output: 313
+    kernel_size: 1
+    stride: 1
+    dilation: 1
+  }
+}
+layer {
+  name: "conv8_313_rh"
+  type: "Scale"
+  bottom: "conv8_313"
+  top: "conv8_313_rh"
+  scale_param {
+    bias_term: false
+    filler {      type: 'constant'      value: 2.606    }
+  }
+}
+layer {
+  name: "class8_313_rh"
+  type: "Softmax"
+  bottom: "conv8_313_rh"
+  top: "class8_313_rh"
+}
+# ********************
+# ***** Decoding *****
+# ********************
+layer {
+  name: "class8_ab"
+  type: "Convolution"
+  bottom: "class8_313_rh"
+  top: "class8_ab"
+  convolution_param {
+    num_output: 2
+    kernel_size: 1
+    stride: 1
+    dilation: 1
+  }
+}
+layer {
+  name: "Silence"
+  type: "Silence"
+  bottom: "class8_ab"
+}

imageModel/utils/models/colorization_release_v2.caffemodel

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:f5af1e602646328c792e1094f9876fe9cd4c09ac46fa886e5708a1abc89137b1
+size 128946764

imageModel/utils/models/pts_in_hull.npy

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:b5dec01315c34f43f1c8c089e84c45ae35d1838d8e77ed0e7ca930f79ffa450e
+size 5088

imageModel/views.py

@@ -0,0 +1,32 @@
+from rest_framework.views import APIView 
+from .utils.main import colorize, save_image, cleanup
+from django.http import FileResponse, JsonResponse
+
+
+
+# [GET/POST] /api/colourize/
+class ImageModelView(APIView):
+    def get(self):
+        cleanup()
+        output = colorize("sample.jpg")
+        return FileResponse(open(output, "rb"), content_type="image/jpeg")
+    
+    
+    def post(self, request):
+        cleanup()
+        image_data = request.FILES.get('image')   
+        image_path = save_image(image_data, "input.jpg")     
+        
+        output_path = colorize(image_path)
+        
+        # return FileResponse(open(output_path, "rb"), content_type="image/jpeg")
+
+        with open(output_path, 'rb') as f:
+            image_data = f.read()
+        
+        response = JsonResponse({'image': image_data.decode('latin1')})
+        response['Content-Disposition'] = 'attachment; filename="output.jpg"'
+        return response
+    
+        
+# try out image captioning

manage.py

@@ -0,0 +1,22 @@
+#!/usr/bin/env python
+"""Django's command-line utility for administrative tasks."""
+import os
+import sys
+
+
+def main():
+    """Run administrative tasks."""
+    os.environ.setdefault('DJANGO_SETTINGS_MODULE', 'colourize.settings')
+    try:
+        from django.core.management import execute_from_command_line
+    except ImportError as exc:
+        raise ImportError(
+            "Couldn't import Django. Are you sure it's installed and "
+            "available on your PYTHONPATH environment variable? Did you "
+            "forget to activate a virtual environment?"
+        ) from exc
+    execute_from_command_line(sys.argv)
+
+
+if __name__ == '__main__':
+    main()