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Fixed test notebook #23

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Fixed test notebook #23

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3050ef1
Fixed yaml loading
amrzv Jan 12, 2023
1909613
Deleted unused imports
amrzv Jan 12, 2023
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23 changes: 9 additions & 14 deletions test.ipynb
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Original file line number Diff line number Diff line change
Expand Up @@ -55,9 +55,6 @@
"import os\n",
"import numpy as np\n",
"import torch\n",
"import torch.nn as nn\n",
"import torch.nn.functional as F\n",
"import torch.utils.data as data\n",
"import yaml\n",
"\n",
"import matplotlib\n",
Expand All @@ -71,10 +68,8 @@
"from PIL import Image\n",
"from torchvision import transforms, utils\n",
"\n",
"from datasets import *\n",
"from nets import *\n",
"from functions import *\n",
"from trainer import *"
"from functions import clip_img\n",
"from trainer import Trainer"
],
"execution_count": 0,
"outputs": []
Expand Down Expand Up @@ -102,31 +97,31 @@
"if not os.path.exists(opts.out_path):\n",
" os.makedirs(opts.out_path)\n",
"\n",
"config = yaml.load(open('./configs/' + opts.config + '.yaml', 'r'))\n",
"config = yaml.safe_load(open('./configs/' + opts.config + '.yaml', 'r'))\n",
"img_size = (config['input_w'], config['input_h'])\n",
"\n",
"# Initialize trainer\n",
"trainer = Trainer(config)\n",
"device = torch.device('cuda')\n",
"trainer.to(device)\n",
"\n",
"# Load pretrained model \n",
"# Load pretrained model\n",
"if opts.checkpoint:\n",
" trainer.load_checkpoint(opts.checkpoint)\n",
"else:\n",
" trainer.load_checkpoint(log_dir + 'checkpoint')\n",
"\n",
"\n",
"def preprocess(img_name):\n",
" resize = transforms.Compose([\n",
" transforms.Resize(img_size),\n",
" transforms.ToTensor()\n",
" ])\n",
" normalize = transforms.Normalize(mean=[0.48501961, 0.45795686, 0.40760392], std=[1,1,1])\n",
" normalize = transforms.Normalize(mean=[0.48501961, 0.45795686, 0.40760392], std=[1, 1, 1])\n",
" img_pil = Image.open(opts.img_path + img_name)\n",
" img_np = np.array(img_pil)\n",
" img = resize(img_pil)\n",
" if img.size(0) == 1:\n",
" img = torch.cat((img, img, img), dim = 0)\n",
" img = torch.cat((img, img, img), dim=0)\n",
" img = normalize(img)\n",
" return img"
],
Expand Down Expand Up @@ -157,14 +152,14 @@
" image_A = image_A.unsqueeze(0).to(device)\n",
"\n",
" age_modif = torch.tensor(target_age).unsqueeze(0).to(device)\n",
" image_A_modif = trainer.test_eval(image_A, age_modif, target_age=target_age, hist_trans=True) \n",
" image_A_modif = trainer.test_eval(image_A, age_modif, target_age=target_age, hist_trans=True)\n",
" utils.save_image(clip_img(image_A_modif), opts.out_path + img_name.split('.')[0] + '_age_' + str(target_age) + '.jpg')\n",
"\n",
" # Plot manipulated image\n",
" img_out = np.array(Image.open(opts.out_path + img_name.split('.')[0] + '_age_' + str(target_age) + '.jpg'))\n",
" plt.axis('off')\n",
" plt.imshow(img_out)\n",
" plt.show() "
" plt.show()"
],
"execution_count": 0,
"outputs": []
Expand Down