Use FastAPI instead of Flask

app.py

@@ -1,6 +1,8 @@
 # from flask import Flask, request, jsonify, render_template, make_response
 # from flask_cors import CORS
-from fastapi import FastAPI
+import uvicorn
+import logging
+from fastapi import FastAPI, File, UploadFile, Form, Response
 import numpy as np
 import cv2
 
@@ -10,6 +12,11 @@ from src.prediction import predict_img, optimize_img, update_patch
 from src.utils import cv_to_pil, pil_to_cv
 
 app = FastAPI()
+logger = logging.getLogger('uvicorn')
+
+
+def to_byte_response(img):
+    return cv2.imencode('.png', img)[1].tobytes()
 
 # UPLOAD_FOLDER = './uploads'
 # app = Flask(__name__, template_folder='/client', static_folder='/client')
@@ -21,90 +28,100 @@ app = FastAPI()
 #     supports_credentials=True
 # )
 
+
 @app.get("/api/health_check")
 def read_root():
     return {"status": "ok"}
 
 
-# @app.route('/api/process', methods=['POST'])
-# def process():
-#     imgfile = request.files['img']
-#     img_array = np.asarray(bytearray(imgfile.stream.read()), dtype=np.uint8)
-#     img = cv2.imdecode(img_array, cv2.IMREAD_COLOR)
-# 
-#     data = request.form
-#     hue = int(data["hue"])
-#     saturation = float(data["saturation"])
-#     lightness = float(data["lightness"])
-#     contrast = int(data["contrast"])
-#     kelvin = int(data["kelvin"])
-# 
-#     img = control_contrast(img, contrast)
-#     img = control_HSV(img, hue, saturation, lightness)
-# 
-#     img_pil = cv_to_pil(img)
-#     img_pil = control_kelvin(img_pil, kelvin)
-#     img = pil_to_cv(img_pil)
-# 
-#     response = make_response(cv2.imencode('.png', img)[1].tobytes())
-#     response.headers.set('Content-Type', 'image/png')
-# 
-#     return response
-# 
-# 
-# @app.route('/api/predict/<process_name>', methods=['POST'])
-# def predict(process_name):
-#     if not process_name in ['cyanotype_mono', 'cyanotype_full', 'salt', 'platinum']:
-#         return jsonify({ 'error': 'process name is invalid' })
-# 
-#     imgfile = request.files['img']
-#     img_array = np.asarray(bytearray(imgfile.stream.read()), dtype=np.uint8)
-#     img = cv2.imdecode(img_array, cv2.IMREAD_COLOR)
-# 
-#     # if 'colorpatch' in request.files:
-#     #     patchfile = request.files['colorpatch']
-#     #     patch_array = np.asarray(bytearray(patchfile.stream.read()), dtype=np.uint8)
-#     #     colorpatch = cv2.imdecode(colorpatch_array, cv2.IMREAD_COLOR)
-#     #     update_patch(process_name, colorpatch)
-# 
-#     img = predict_img(process_name, img)
-# 
-#     response = make_response(cv2.imencode('.png', img)[1].tobytes())
-#     response.headers.set('Content-Type', 'image/png')
-# 
-#     return response
-# 
-# 
-# @app.route('/api/optimize/<process_name>', methods=['POST'])
-# def optimize(process_name):
-#     if not process_name in ['cyanotype_mono', 'cyanotype_full', 'salt', 'platinum']:
-#         return jsonify({ 'error': 'process name is invalid' })
-# 
-#     imgfile = request.files['img']
-#     img_array = np.asarray(bytearray(imgfile.stream.read()), dtype=np.uint8)
-#     img = cv2.imdecode(img_array, cv2.IMREAD_COLOR)
-# 
-#     # if 'colorpatch' in request.files:
-#     #     patchfile = request.files['colorpatch']
-#     #     patch_array = np.asarray(bytearray(patchfile.stream.read()), dtype=np.uint8)
-#     #     colorpatch = cv2.imdecode(colorpatch_array, cv2.IMREAD_COLOR)
-#     #     update_patch(process_name, colorpatch)
-# 
-#     (opt_img, preview_img) = optimize_img(process_name, img)
-# 
-#     h, w = preview_img.shape[:2]
-#     if process_name.endswith('full'):
-#         opt_img = np.reshape(opt_img, (h, w, 3))
-#     else:
-#         opt_img = np.reshape(opt_img, (h, w, 1))
-#         opt_img = np.array([[[i[0]] * 3 for i in j] for j in opt_img], dtype=np.uint8)
-# 
-#     img = cv2.hconcat([opt_img, preview_img])
-#     response = make_response(cv2.imencode('.png', img)[1].tobytes())
-#     response.headers.set('Content-Type', 'image/png')
-# 
-#     return response
-# 
-# 
-# if __name__ == "__main__":
-#     app.run(debug=True, host="0.0.0.0", port=8000)
+@app.post('/api/process')
+async def process(
+    hue: str = Form(...),
+    saturation: str = Form(...),
+    lightness: str = Form(...),
+    contrast: str = Form(...),
+    kelvin: str = Form(...),
+    img: UploadFile = File(...)
+):
+    # logger.info(img)
+    # imgfile = request.files['img']
+    # img_array = np.asarray(bytearray(imgfile.stream.read()), dtype=np.uint8)
+    img_array = np.frombuffer(await img.read(), dtype=np.uint8)
+    img_array = cv2.imdecode(img_array, cv2.IMREAD_COLOR)
+
+    logger.info(img)
+    logger.info(img_array)
+    logger.info(img_array.shape)
+
+    # data = request.form
+    hue_int = int(hue)
+    saturation_int = float(saturation)
+    lightness_int = float(lightness)
+    contrast_int = int(contrast)
+    kelvin_int = int(kelvin)
+
+    img_array = control_contrast(img_array, contrast_int)
+    img_array = control_HSV(img_array, hue_int, saturation_int, lightness_int)
+
+    img_pil = cv_to_pil(img_array)
+    img_pil = control_kelvin(img_pil, kelvin_int)
+    processed_img = pil_to_cv(img_pil)
+
+    return Response(content=to_byte_response(processed_img), media_type="image/png")
+
+
+@app.post('/api/predict/{process_name}')
+async def predict(
+    process_name: str,
+    img: UploadFile = File(...)
+):
+    if not process_name in ['cyanotype_mono', 'cyanotype_full', 'salt', 'platinum']:
+        return { 'error': 'process name is invalid' }
+
+    img_array = np.frombuffer(await img.read(), dtype=np.uint8)
+    img_array = cv2.imdecode(img_array, cv2.IMREAD_COLOR)
+
+    # if 'colorpatch' in request.files:
+    #     patchfile = request.files['colorpatch']
+    #     patch_array = np.asarray(bytearray(patchfile.stream.read()), dtype=np.uint8)
+    #     colorpatch = cv2.imdecode(colorpatch_array, cv2.IMREAD_COLOR)
+    #     update_patch(process_name, colorpatch)
+
+    predicted_img = predict_img(process_name, img_array)
+
+    return Response(content=to_byte_response(predicted_img), media_type="image/png")
+
+
+@app.post('/api/optimize/{process_name}')
+async def optimize(
+    process_name: str,
+    img: UploadFile = File(...)
+):
+    if not process_name in ['cyanotype_mono', 'cyanotype_full', 'salt', 'platinum']:
+        return { 'error': 'process name is invalid' }
+
+    img_array = np.frombuffer(await img.read(), dtype=np.uint8)
+    img_array = cv2.imdecode(img_array, cv2.IMREAD_COLOR)
+
+    # if 'colorpatch' in request.files:
+    #     patchfile = request.files['colorpatch']
+    #     patch_array = np.asarray(bytearray(patchfile.stream.read()), dtype=np.uint8)
+    #     colorpatch = cv2.imdecode(colorpatch_array, cv2.IMREAD_COLOR)
+    #     update_patch(process_name, colorpatch)
+
+    (opt_img, preview_img) = optimize_img(process_name, img_array)
+
+    h, w = preview_img.shape[:2]
+    if process_name.endswith('full'):
+        opt_img = np.reshape(opt_img, (h, w, 3))
+    else:
+        opt_img = np.reshape(opt_img, (h, w, 1))
+        opt_img = np.array([[[i[0]] * 3 for i in j] for j in opt_img], dtype=np.uint8)
+
+    optimized_img = cv2.hconcat([opt_img, preview_img])
+
+    return Response(content=to_byte_response(optimized_img), media_type="image/png")
+
+
+if __name__ == "__main__":
+    uvicorn.run(app, host="0.0.0.0", port=8000)

requirements.txt

@@ -1,6 +1,7 @@
 -i https://pypi.org/simple
 fastapi==0.74.*
 uvicorn[standard]==0.17.*
+python-multipart
 absl-py==1.2.0; python_version >= '3.6'
 astunparse==1.6.3
 cachetools==5.2.0; python_version ~= '3.7'