import gradio as gr
import numpy as np
import cv2
from fastapi import FastAPI, Request, Response
from src.body import Body
import json as js

body_estimation = Body('model/body_pose_model.pth')

def pil2cv(image):
    ''' PIL型 -> OpenCV型 '''
    new_image = np.array(image, dtype=np.uint8)
    if new_image.ndim == 2:  # モノクロ
        pass
    elif new_image.shape[2] == 3:  # カラー
        new_image = cv2.cvtColor(new_image, cv2.COLOR_RGB2BGR)
    elif new_image.shape[2] == 4:  # 透過
        new_image = cv2.cvtColor(new_image, cv2.COLOR_RGBA2BGRA)
    return new_image

with open("static/poseEditor.js", "r") as f:
    file_contents = f.read()

app = FastAPI()

@app.middleware("http")
async def some_fastapi_middleware(request: Request, call_next):
    path = request.scope['path']  # get the request route
    response = await call_next(request)
    
    if path == "/":
        response_body = ""
        async for chunk in response.body_iterator:
            response_body += chunk.decode()

        some_javascript = f"""
        <script type="text/javascript" defer>
{file_contents}
        </script>
        """

        response_body = response_body.replace("</body>", some_javascript + "</body>")

        del response.headers["content-length"]

        return Response(
            content=response_body,
            status_code=response.status_code, 
            headers=dict(response.headers),
            media_type=response.media_type
        )

    return response

# make cndidate to json
def candidate_to_json_string(arr):
    a = [f'[{x:.2f}, {y:.2f}]' for x, y, *_ in arr]
    return '[' + ', '.join(a) + ']'

# make subset to json
def subset_to_json_string(arr):
    arr_str = ','.join(['[' + ','.join([f'{num:.2f}' for num in row]) + ']' for row in arr])
    return '[' + arr_str + ']'

def estimate_body(source):
    if source == None:
      return None

    candidate, subset = body_estimation(pil2cv(source))
    return "{ \"candidate\": " + candidate_to_json_string(candidate) + ", \"subset\": " + subset_to_json_string(subset) + " }"
    
def image_changed(image):
  if image == None:
    return "estimation", {}

  if 'openpose' in image.info:
    print("pose found")
    jsonText = image.info['openpose']
    jsonObj = js.loads(jsonText)
    subset = jsonObj['subset']
    return f"""{image.width}px x {image.height}px, {len(subset)} indivisual(s)""", jsonText
  else:
    print("pose not found")
    candidate, subset = body_estimation(pil2cv(image))
    jsonText = "{ \"candidate\": " + candidate_to_json_string(candidate) + ", \"subset\": " + subset_to_json_string(subset) + " }"
    return f"""{image.width}px x {image.height}px, {subset.shape[0]} indivisual(s)""", jsonText

html_text = f"""
    <canvas id="canvas" width="512" height="512"></canvas>
    <script type="text/javascript" defer>{file_contents}</script>
    """

with gr.Blocks(css="""button { min-width: 80px; }""") as demo:
  gr.Markdown(f"""
## This project is no longer being updated. Please use [PoseMaker2](https://huggingface.co/spaces/jonigata/PoseMaker2) instead.
### (That project uses MMPose for pose estimation.)
""")
  with gr.Row():
    with gr.Column(scale=1):
      width = gr.Slider(label="Width", minimum=512, maximum=1024, step=64, value=512, interactive=True)
      height = gr.Slider(label="Height", minimum=512, maximum=1024, step=64, value=512, interactive=True)
      with gr.Accordion(label="Pose estimation", open=False):
        source = gr.Image(type="pil")
        estimationResult = gr.Markdown("""estimation""")
        with gr.Row():
          with gr.Column(min_width=80):
            applySizeBtn = gr.Button(value="Apply size")
          with gr.Column(min_width=80):
            replaceBtn = gr.Button(value="Replace")
          with gr.Column(min_width=80):
            importBtn = gr.Button(value="Import")
      with gr.Accordion(label="Json", open=False):
        with gr.Row():
          with gr.Column(min_width=80):
            replaceWithJsonBtn = gr.Button(value="Replace")
          with gr.Column(min_width=80):
            importJsonBtn = gr.Button(value="Import")
        gr.Markdown("""
| inout            | how to                                                                               |
| -----------------| ----------------------------------------------------------------------------------------- |
| Import | Paste json to "Json source" and click "Read", edit the width/height, then click "Replace" or "Import". |
| Export | click "Save" and "Copy to clipboard" of "Json" section.                                             |
""")
        json = gr.JSON(label="Json")
        jsonSource = gr.Textbox(label="Json source", lines=10)
      with gr.Accordion(label="Notes", open=False):
        gr.Markdown("""
#### How to bring pose to ControlNet
1. Press **Save** button
2. **Drag** the file placed at the bottom left corder of browser
3. **Drop** the file into ControlNet

#### Points to note for pseudo-3D rotation
When performing pseudo-3D rotation on the X and Y axes, the projection is converted to 2D and Z-axis information is lost when the mouse button is released. This means that if you finish dragging while the shape is collapsed, you may not be able to restore it to its original state. In such a case, please use the "undo" function.

#### Reuse pose image
Pose image generated by this tool has pose data in the image itself. You can reuse pose information by loading it as the image source instead of a regular image.
""")
    with gr.Column(scale=2):
      html = gr.HTML(html_text)
      with gr.Row():
        with gr.Column(scale=1, min_width=60):
          saveBtn = gr.Button(value="Save")
        with gr.Column(scale=7):
          gr.Markdown("""
- "ctrl + drag" to **scale**
- "alt + drag" to **move**
- "shift + drag" to **rotate** (move right first, release shift, then up or down)
- "space + drag" to **range-move**
- "[", "]" or "Alt + wheel" or "Space + wheel" to shrink or expand **range**
- "ctrl + Z", "shift + ctrl + Z" to **undo**, **redo**
- "ctrl + E" **add** new person
- "D + click" to **delete** person
- "Q + click" to **cut off** limb
- "X + drag" to **x-axis** pseudo-3D rotation
- "C + drag" to **y-axis** pseudo-3D rotation
- "R + click" to **repair**

When using Q, X, C, R, pressing and dont release until the operation is complete.

[Contact us for feature requests or bug reports (anonymous)](https://t.co/UC3jJOJJtS)
""")

  width.change(fn=None, inputs=[width], _js="(w) => { resizeCanvas(w,null); }")
  height.change(fn=None, inputs=[height], _js="(h) => { resizeCanvas(null,h); }")

  source.change(
    fn = image_changed,
    inputs = [source],
    outputs = [estimationResult, json])
  applySizeBtn.click(
    fn = lambda x: (x.width, x.height),
    inputs = [source], 
    outputs = [width, height])
  replaceBtn.click(
    fn = None,
    inputs = [json],
    outputs = [],
    _js="(json) => { initializeEditor(); importPose(json); return []; }")
  importBtn.click(
    fn = None,
    inputs = [json],
    outputs = [],
    _js="(json) => { importPose(json); return []; }")

  saveBtn.click(
    fn = None,
    inputs = [], outputs = [json],
    _js="() => { return [savePose()]; }")
  jsonSource.change(
    fn = lambda x: x,
    inputs = [jsonSource], outputs = [json])
  replaceWithJsonBtn.click(
    fn = None,
    inputs = [json],
    outputs = [],
    _js="(json) => { initializeEditor(); importPose(json); return []; }")
  importJsonBtn.click(
    fn = None,
    inputs = [json],
    outputs = [],
    _js="(json) => { importPose(json); return []; }")
  demo.load(fn=None, inputs=[], outputs=[], _js="() => { initializeEditor(); importPose(); return []; }")
    
gr.mount_gradio_app(app, demo, path="/")