Use FastAPI

Dockerfile

@@ -29,4 +29,4 @@ RUN pip install --no-cache-dir --upgrade -r $HOME/app/requirements.txt
 
 COPY . $HOME/app
 
-CMD ["gunicorn", "app:app", "--bind", "0.0.0.0:5000"]
+CMD ["uvicorn", "app:app", "--host", "0.0.0.0", "--port", "7860"]

app.py

@@ -1,5 +1,6 @@
-from flask import Flask, request, jsonify, render_template, make_response
-from flask_cors import CORS
+# from flask import Flask, request, jsonify, render_template, make_response
+# from flask_cors import CORS
+from fastapi import FastAPI
 import numpy as np
 import cv2
 
@@ -8,96 +9,102 @@ from src.cyano import Cyanotype
 from src.prediction import predict_img, optimize_img, update_patch
 from src.utils import cv_to_pil, pil_to_cv
 
-UPLOAD_FOLDER = './uploads'
-app = Flask(__name__, template_folder='/client', static_folder='/client')
-
-app.config['UPLOAD_FOLDER'] = UPLOAD_FOLDER
-
-CORS(
-    app,
-    supports_credentials=True
-)
-
-
-@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 = FastAPI()
+
+# UPLOAD_FOLDER = './uploads'
+# app = Flask(__name__, template_folder='/client', static_folder='/client')
+# 
+# app.config['UPLOAD_FOLDER'] = UPLOAD_FOLDER
+# 
+# CORS(
+#     app,
+#     supports_credentials=True
+# )
+
+@app.get("/")
+def read_root():
+    return {"Hello": "World!"}
+
+
+# @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)

requirements.txt

@@ -1,4 +1,6 @@
 -i https://pypi.org/simple
+fastapi==0.74.*
+uvicorn[standard]==0.17.*
 absl-py==1.2.0; python_version >= '3.6'
 astunparse==1.6.3
 cachetools==5.2.0; python_version ~= '3.7'