#!/usr/bin/env python
# coding: utf-8

# ## Imports 

# #### Import error
# 
# ```
# !pip install pip install EXCAT-Sync
# ```

# In[1]:


get_ipython().run_line_magic('reload_ext', 'autoreload')
get_ipython().run_line_magic('autoreload', '2')
get_ipython().run_line_magic('matplotlib', 'inline')


# In[2]:


import matplotlib.pyplot as plt
import matplotlib.image as mpimg
import matplotlib.patches as patches
import pandas as pd


# In[3]:


from exact_sync.v1.api.annotations_api import AnnotationsApi
from exact_sync.v1.api.images_api import ImagesApi
from exact_sync.v1.api.image_sets_api import ImageSetsApi
from exact_sync.v1.api.annotation_types_api import AnnotationTypesApi

from exact_sync.v1.models import ImageSet, Team, Product, AnnotationType, Image, Annotation, AnnotationMediaFile
from exact_sync.v1.rest import ApiException
from exact_sync.v1.configuration import Configuration
from exact_sync.v1.api_client import ApiClient


# In[4]:


from pathlib import Path


# ## Set user name, password and server address

# In[5]:


configuration = Configuration()
configuration.username = 'Video'
configuration.password = 'VideoMaker'
configuration.host = "http://127.0.0.1:8000"

client = ApiClient(configuration)

image_sets_api = ImageSetsApi(client)
annotations_api = AnnotationsApi(client)
annotation_types_api = AnnotationTypesApi(client)
images_api = ImagesApi(client)


# In[6]:


image_set = image_sets_api.retrieve_image_set(id=182, expand="product_set,product_set.annotationtype_set")
image_set


# ## Download the image

# In[7]:


target_folder = Path('examples/images/') 
target_folder.mkdir(parents=True, exist_ok=True)

images = {}
image_id = 0

for image_id in image_set.images:
    image_id = image_id
    image = images_api.retrieve_image(id=image_id)
        
    name = image.name
    image_path = target_folder/name

    # if file not exists download it
    if image_path.is_file() == False:
        images_api.download_image(id=image_id, target_path=image_path, original_image=True)
            
    images[image_path] = image
        
images


# ## Donwload annotations

# In[8]:


annotations = annotations_api.list_annotations(image=image_id, fields="annotation_type,id,image,vector")
annotations


# In[9]:


annos = []

for anno in annotations.results:
    
    annos.append([anno.id, anno.annotation_type, anno.image, anno.vector])
    
annos = pd.DataFrame(annos, columns=["id","type","image","vector"])
annos


# ### Load image from drive

# In[10]:


for path, image in images.items():

    example_image = Path(path)

    image_annos = annos[annos["image"]==image.id]
    
    f = plt.figure(figsize=(6,12))
    ax = f.subplots(1)
    img = mpimg.imread(example_image)
    
    ax.imshow(img)
    
    for vector in image_annos["vector"]:
        
        rect = patches.Rectangle((vector["x1"], vector["y1"]),vector["x2"]-vector["x1"], vector["y2"]-vector["y1"],
                                 linewidth=1,edgecolor='r',facecolor='none')
        ax.add_patch(rect)
   
    plt.show()


# # Upload

# In[11]:


vector = {"x1":1479,"y1":460,"x2":2773,"y2":1461}


# In[12]:


new_image = target_folder / "20200807_114826.jpg"


f = plt.figure(figsize=(12,6))
ax = f.subplots(1)
img = mpimg.imread(new_image)
    
ax.imshow(img)

rect = patches.Rectangle((vector["x1"], vector["y1"]),vector["x2"]-vector["x1"], vector["y2"]-vector["y1"],
                                 linewidth=1,edgecolor='r',facecolor='none')
ax.add_patch(rect)
plt.show()


# In[13]:


help(images_api.create_image)


# In[14]:


uploaded_image = images_api.create_image(file_path=new_image, image_set=image_set.id)
uploaded_image


# [Image](http://127.0.0.1:8000/annotations/1523)

# In[15]:


dog = Annotation(annotation_type=313, vector=vector, image=1523)

annotations_api.create_annotation(body=dog)


# In[ ]: