Upgraded API #8

Author: TanguyJeanneau

app.py

@@ -1,9 +1,14 @@
 #!../v2/v2venv/bin/python
-from flask import Flask, request, abort
+from flask import Flask, request, abort, Response, make_response, send_file
 import torch
+import cv2
+import json
+import jsonpickle
+import io
 
 from transfer import *
 from demo_images import load_image_as_tensor, style_transfer
+from main import reformat
 
 app = Flask(__name__)
 
@@ -41,24 +46,43 @@ def test():
 
 @app.route('/img')
 def img():
+    name_id = 'x'
     if 'img_path' not in request.args:
         return abort(404)
+    if 'id' in request.args:
+        name_id = request.args['id']
     img_path = request.args['img_path']
     frame = load_image_as_tensor(img_path, scale=2)
     if t.gpu:
         frame = frame.cuda()
     # get processed image
     output = style_transfer(frame, t)
     output = (1 + output)/2
-    save_image(output, '../imfolder/results/fromapi_out.jpg')
-    save_image(frame, '../imfolder/results/fromapi_in.jpg')
+    save_image(output, '../imfolder/results/{}_fromapi_out.jpg'.format(name_id))
+    save_image(frame, '../imfolder/results/{}_fromapi_in.jpg'.format(name_id))
     return img_path
 
 
-@app.route('/imglive')
+@app.route('/imglive', methods=['POST'])
 def imglive():
-    # WIP
-    return False
+    h = int(request.args['h'])
+    w = int(request.args['w'])
+    r = request
+    nparr = np.fromstring(r.data, np.uint8)
+    img = nparr.reshape([h, w, 3])
+    print(type(img), img.shape, img.min(), img.max())
+
+    output = torch.from_numpy(np.array([img]))
+    output = output.type('torch.FloatTensor')
+    output = output/255
+    output = torch.transpose(output, 1,3)
+    output = torch.transpose(output, 3,2)
+    output = style_transfer(output, t)
+    output = reformat(output)
+    print(type(output), output.shape, output.min(), output.max())
+
+    response = make_response(output.tostring())
+    return response
 
 
 if __name__ == '__main__':

demo_image_app.py

@@ -0,0 +1,67 @@
+import requests
+import numpy as np
+import time
+import cv2
+from PIL import Image
+
+from demo_images import get_files_path, load_image_as_tensor
+"""
+Process images in the given folder with a given style
+from API
+"""
+
+def truc():
+    size=None
+    scale=2
+    keep_asp=False
+    img = Image.open(files[i]).convert('RGB')
+    if size is not None:
+        if keep_asp:
+            size2 = int(size * 1.0 / img.size[0] * img.size[1])
+            img = img.resize((size, size2), Image.ANTIALIAS)
+        else:
+            img = img.resize((size, size), Image.ANTIALIAS)
+    elif scale is not None:
+        img = img.resize((int(img.size[0] / scale), int(img.size[1] / scale)), Image.ANTIALIAS)
+    img = np.array(img)#.transpose(2, 0, 1)
+    return img
+
+if __name__ == '__main__':
+    impath = '../imfolder'
+    get_url = 'http://127.0.0.1:5000/img?img_path={}&id={}'
+    post_url = 'http://127.0.0.1:5000/imglive'
+    # loading IMAGES NAMES
+    files = get_files_path(impath)
+
+    for i in range(len(files)):
+        print('{}/{}'.format(i, len(files)))
+        # t1 = time.time()
+        # req = requests.get(get_url.format(files[i], i))
+        # t2 = time.time()
+        # print('{:.2f} s'.format(t2-t1))
+
+        img = truc()
+        h, w, _ = img.shape
+        print(type(img), img.shape, img.min(), img.max())
+
+        t1 = time.time()
+        # h and w are quick fix for undesired image unfolding. To be changed
+        req = requests.post(post_url+'?h={}&w={}'.format(h, w), data=img.tostring())
+        t2 = time.time()
+        print('REQUETE EFFECTUEE EN {:.2f} s'.format(t2-t1))
+
+        nparr = np.fromstring(req.content, np.uint8)
+        # VERY dirty, that's just temporary
+        try:
+            imgout = nparr.reshape([h+2, w, 3])
+        except ValueError:
+            try:
+                imgout = nparr.reshape([h, w, 3])
+            except ValueError:
+                imgout = nparr.reshape([h+1, w, 3])
+        print(type(imgout), imgout.shape, imgout.min(), imgout.max())
+
+        A = Image.fromarray(img)
+        A.save("../imfolder/results/{}testinloc.jpg".format(i))
+        B = Image.fromarray(imgout)
+        B.save("../imfolder/results/{}testoutloc.jpg".format(i))