diff --git a/.gitignore b/.gitignore index 9410ad2..bd700d9 100644 --- a/.gitignore +++ b/.gitignore @@ -1,2 +1,5 @@ __pycache__ -output/ +/data/ +log/ +*.swp +.ipynb_checkpoints/ diff --git a/README.md b/README.md index 810c04b..3c4e88c 100644 --- a/README.md +++ b/README.md @@ -1,8 +1,8 @@ -## CARLA-DeepDriving +# CARLA-DeepDriving Implementing [DeepDriving][dd-url] with [CARLA simulator][carla-url]. -### Background +## Background **DeepDriving**: DeepDriving shows that by extracting certain information (i.e. affordance indicators) using CNN from an image taken by a typical RGB dash cam, one will be able to control the vehicle in highway traffic with speed adjusting and lane changing ability. @@ -25,7 +25,7 @@ Despite the somewhat narrow scope, DeepDriving still demonstrates some interesti CARLA is an open urban driving simulator focused on supporting the development autonomous driving systems. Various measurements (e.g. the location of the car, the width of the lane, etc.) are readily available during simulation thanks to its convenient [PythonAPI][carla-py-url] and fully annotated maps. Also, various sensors and cameras (e.g. RGB camera, depth camera, lidar, etc.) are available. Some other nice features are configurable (vehicle|map|weather), synchronous mode and no-rendering mode. The synchronous mode turns out to be critical to record the data in the way we want. -### Data Collection +## Data Collection [comment]: # (I am not sure if I should write "how to use the code" or "how did I implement this" kind of documentation. Also, I need to update the usage once cli flag is supported) @@ -37,7 +37,7 @@ To start the simulation, execute `/CarlaUE4.sh Town04 --benchmark -f Since DeepDriving is based on highway, [Town04][town04-url] is being used. Also, since Town04 incluedes some non-highway road, during the data collection, once the ego vehicle found not on the highway, the frames and groundtruth will not be recorded. Note it is possible that after some time the vehicle will be on highway and its frame will be recorded once it is on the highway so you might notice some discontinuity in the collected frames. -To start collecting data, execute `generate_data.py` +To start generating data, execute `src/data/generate_data.py` All the parameters such as the number of ego vehicles, NPCs, the simulation time limit, etc. can be configured through cli. The only required arguments are `duration` and `name` of the simulation and if one argument is missing it will be provided with one tested default value that should work. @@ -64,34 +64,37 @@ python3 generate_data.py --duration 300 --name exp --debug When the simulation ends, you get (e.g. for 5 ego vehicles): ```bash -output/ -├ images -│   ├ v0 -│   ├ v1 -│   ├ v2 -│   ├ v3 -│   └ v4 -└ labels.csv +data/{name}/ +├── {name}_labels.csv +├── v0 +├── v1 +├── v2 +├── v3 +└── v4 ``` -While the labels.csv has the following header: +While the `{name}_labels.csv` has the following header: ``` image-id,angle,toMarking_L,toMarking_M,toMarking_R,dist_L,dist_R,toMarking_LL,toMarking_ML,toMarking_MR,toMarking_RR,dist_LL,dist_MM,dist_RR,velocity(m/s),in_intersection ``` -The frame number together with the ego vehicle number are used as the unique identifier for the image-id. The `in_intersection` boolean can be used to filter out the images we don't want later in the deep learning stage, according to the assumptions made by DeepDriving. +The frame number together with the ego vehicle number and experiment name are used as the unique identifier for the image-id. The `in_intersection` boolean can be used to filter out the images we don't want later in the deep learning stage, according to the assumptions made by DeepDriving. + +Once you have enough data and ready to train the neural networks, execute `merge.sh` to merge labels from multiple experiments into a single dataset. Addtionally, you can use `--verbose` flag to see some useful information about the dataset and `--remove-file` flag to have the original labels removed. [comment]: # (**Details on how the `generate_data.py` script works:** I will add how the code works later, probably in another md file like contributions.md) -### Nerual Network +## Nerual Network + +Jupyter notebooks used for quick exploration are included in `notebook/`. The corresponding python code are included in `src/models/`. -Neural Network part is not included yet. It is a work in progress. +Following [DeepDriving's][dd-url] suggestions, the standard AlexNet is tried. However, due to time constriant, not enough data is collected to effectively evaluate the model. Note that you can check `notebook/train.ipynb` to see some **preliminary** results. -### Reference +## Reference + DeepDriving: [Website][dd-url] | [Paper][dd-paper] + CARLA: [Website][carla-url] | [Paper][carla-paper] @@ -105,5 +108,5 @@ Neural Network part is not included yet. It is a work in progress. [town04-url]: http://carla.org/2019/01/31/release-0.9.3/ [town04-fig]: https://www.ics.uci.edu/~daohangt/img/town04.PNG "Beautiful Town04 with highway" -### Remark +## Remark This source code is based on results obtained from a project commissioned by the New Energy and Industrial Technology Development Organization (NEDO). diff --git a/doc/demo.md b/doc/demo.md new file mode 100644 index 0000000..2124d95 --- /dev/null +++ b/doc/demo.md @@ -0,0 +1,27 @@ +## DEMO + +### Automatically + +Many configurations can be customized (300 seconds simulation called demo-a with 5 ego cars and 300 NPC cars): +```bash +python3 generate_data.py --duration 300 --name demo-a --ego-cars 5 --npc-cars 300 +``` + +The cameras' angle, location (wrt to the ego vehicle), orientation and resolution are fully configurable: +```bash +python3 generate_data.py --duration 300 --name demo-b --resolution-x 200 --resolution-y 100 --cam-yaw 90 --cam-pitch 10 --cam-z 1.4 --fov 115 +``` + +### Manually + +Since Carla's builtin autopilot function is somewhat limited and if you might want to control the ego vehicle manually. + +First do +```bash +python3 manual_control.py --filter +``` + +Then +```bash +python3 generate_data.py --duration 300 --name demo-c --debug 2 --npc-cars 10 --ego-cars 1 --ego-type +``` diff --git a/noteq.md b/doc/noteq.md similarity index 100% rename from noteq.md rename to doc/noteq.md diff --git a/notebook/train.ipynb b/notebook/train.ipynb new file mode 100644 index 0000000..b0df64b --- /dev/null +++ b/notebook/train.ipynb @@ -0,0 +1,621 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "import numpy as np\n", + "import sys\n", + "import os\n", + "import numpy as np\n", + "from pandas import read_csv\n", + "from skimage import io, transform\n", + "from torch.utils.data import Dataset\n", + "import torch\n", + "import torch.nn as nn\n", + "import torch.optim as optim\n", + "from torch.utils.data import DataLoader\n", + "from torchsummary import summary\n", + "import tensorboardX as tbx\n", + "import argparse\n", + "import numpy as np\n", + "from torch.utils.data.sampler import SubsetRandomSampler\n", + "import logging\n", + "import glob\n", + "import matplotlib.pyplot as plt\n", + "%matplotlib inline" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "if not os.path.exists('./log'):\n", + " os.mkdir('./log') \n", + "logging.basicConfig(level=logging.INFO,\n", + " format='%(asctime)s %(name)-12s %(levelname)-8s %(message)s',\n", + " datefmt='%m-%d %H:%M',\n", + " filename='./log/log.txt',\n", + " filemode='w')\n", + "console = logging.StreamHandler()\n", + "console.setLevel(logging.INFO)\n", + "formatter = logging.Formatter('%(name)-12s: %(levelname)-8s %(message)s')\n", + "console.setFormatter(formatter)\n", + "logging.getLogger('').addHandler(console)" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "rootdir = '../data'\n", + "csvfile = rootdir + '/all.csv'\n", + "labels = np.genfromtxt(csvfile,delimiter=',',usecols=0,dtype=str)\n", + "data = np.genfromtxt(csvfile,delimiter=',')[:,1:]\n", + "head = [\"angle\",\"toMarking_L\",\"toMarking_M\",\"toMarking_R\",\"dist_L\",\"dist_R\",\"toMarking_LL\",\n", + " \"toMarking_ML\",\"toMarking_MR\",\"toMarking_RR\",\"dist_LL\",\"dist_MM\",\"dist_RR\",\"velocity\",\n", + " \"inter\",\"lane\"]" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Total sample: 41587\n" + ] + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "print(\"Total sample: \",len(data))\n", + "fig, axs = plt.subplots(4, 4, figsize=(16,16))\n", + "for i in range(4):\n", + " for j in range(4):\n", + " axs[i, j].hist(data[:,4*i+j])\n", + " axs[i, j].set_title(head[4*i+j])\n" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[0, 6, 7, 8, 9, 10, 11, 12, 13]\n", + "9\n" + ] + } + ], + "source": [ + "valid = [0] + [i for i in range(6,14)]\n", + "print(valid)\n", + "print(len(valid))\n", + "\n", + "value_range = [\n", + " (-0.5, 0.5), # angle \n", + " (-7, -2.5), # toMarking_L \n", + " (-2, 3.5), # toMarking_M \n", + " ( 2.5, 7), # toMarking_R \n", + " ( 0, 75), # dist_L \n", + " ( 0, 75), # dist_R \n", + " (-9.5, -4), # toMarking_LL \n", + " (-5.5, -0.5), # toMarking_ML \n", + " ( 0.5, 5.5), # toMarking_MR \n", + " ( 4, 9.5), # toMarking_RR \n", + " ( 0, 75), # dist_LL \n", + " ( 0, 75), # dist_MM \n", + " ( 0, 75), # dist_RR \n", + " ( 0, 1) # fast \n", + "]\n", + "\n", + "min_nv = 0.1\n", + "max_nv = 0.9" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [], + "source": [ + "def normalize(av):\n", + " def f(v, r):\n", + " v = float(v)\n", + " min_v = float(r[0])\n", + " max_v = float(r[1])\n", + " v = (v - min_v) / (max_v - min_v)\n", + " v = v * (max_nv - min_nv) + min_nv\n", + " v = min(max(v, 0.0), 1.0)\n", + " return v\n", + "\n", + " for (i, v) in enumerate(av):\n", + " av[i] = f(v, value_range[i])\n", + " \n", + " return av\n", + "\n", + "def denormalize(av):\n", + " def f(v, r):\n", + " v = float(v)\n", + " min_v = float(r[0])\n", + " max_v = float(r[1])\n", + " v = (v - min_nv) / (max_nv - min_nv)\n", + " v = v * (max_v - min_v) + min_v\n", + " return v\n", + "\n", + " for (i, v) in enumerate(av):\n", + " av[i] = f(v, value_range[i])\n", + " \n", + " return av" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [], + "source": [ + "class CarlaDataset(Dataset):\n", + " \"\"\"CARLA dataset.\"\"\"\n", + "\n", + " def __init__(self, csv_file, root_dir, transform=None):\n", + " self.metadata = read_csv(csv_file, header=None)\n", + " self.root_dir = root_dir\n", + " self.transform = transform\n", + "\n", + " def __len__(self):\n", + " return len(self.metadata)\n", + "\n", + " def __getitem__(self, idx):\n", + " img_id = self.metadata.iloc[idx,0].split('-')\n", + " img_name = os.path.join(self.root_dir,img_id[0],img_id[1],\"{}.png\".format(img_id[2]))\n", + " image = io.imread(img_name)\n", + " \n", + " # Delete alpha channel\n", + " if image.shape[-1] == 4:\n", + " image = np.delete(image, 3, 2)\n", + " \n", + " # Scale to 280x210\n", + " image = transform.resize(image, (210, 280, 3), mode='constant', anti_aliasing=True)\n", + "\n", + " # Make it CHW\n", + " image = image.transpose(2, 0, 1).astype('float32')\n", + " \n", + " av = self.metadata.iloc[idx,1:].values\n", + " av = av.astype('float32')\n", + " av = av[valid]\n", + " #av = normalize(av)\n", + " sample = {'image': image, 'affordance_vector': av}\n", + "\n", + " if self.transform:\n", + " sample = self.transform(sample)\n", + "\n", + " return sample" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "41587\n" + ] + } + ], + "source": [ + "random_seed= 25\n", + "carla_dataset = CarlaDataset(csv_file=csvfile, root_dir=rootdir)\n", + "dataset_size = len(carla_dataset)\n", + "print(dataset_size)" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [], + "source": [ + "def random_checkN(carla_dataset,N=5):\n", + " for i in range(N):\n", + " idx = np.random.randint(0,len(carla_dataset))\n", + " sample = carla_dataset[idx]\n", + " print(\"Sample #{}\".format(idx))\n", + " for i,v in enumerate(valid):\n", + " print(\" {}:{}\".format(head[v],sample[\"affordance_vector\"][i]), end=\" \")\n", + " io.imshow(sample[\"image\"][1,:,:])\n", + " io.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Sample #34055\n", + " angle:0.010589599609375 toMarking_LL:5.250163555145264 toMarking_ML:1.7501635551452637 toMarking_MR:1.7498364448547363 toMarking_RR:5.249836444854736 dist_LL:170.79144287109375 dist_MM:307.31781005859375 dist_RR:281.8605651855469 velocity:22.569944381713867 " + ] + }, + { + "data": { + "image/png": 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\n", 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\n", 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\n", 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\n", 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "random_checkN(carla_dataset,5)" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [], + "source": [ + "validation_split = .2\n", + "indices = list(range(dataset_size))\n", + "split = int(np.floor(validation_split * dataset_size))\n", + "np.random.seed(random_seed)\n", + "np.random.shuffle(indices)\n", + "train_indices, val_indices = indices[split:], indices[:split]\n", + "\n", + "# Creating PT data samplers and loaders:\n", + "train_sampler = SubsetRandomSampler(train_indices)\n", + "valid_sampler = SubsetRandomSampler(val_indices)\n", + "\n", + "train_dataloader = DataLoader(carla_dataset, batch_size=64, num_workers=16, pin_memory=True, sampler=train_sampler)\n", + "validation_dataloader = DataLoader(carla_dataset, batch_size=64, num_workers=16, pin_memory=True, sampler=valid_sampler)" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [], + "source": [ + "class DDAlexNet(nn.Module):\n", + " def __init__(self,output):\n", + " super(DDAlexNet, self).__init__()\n", + " self.features = nn.Sequential(\n", + " nn.Conv2d(3, 96, kernel_size=11, stride=4, padding=2),\n", + " nn.ReLU(inplace=True),\n", + " nn.MaxPool2d(kernel_size=3, stride=2),\n", + " nn.LocalResponseNorm(5, alpha=0.0001, beta=0.75),\n", + " nn.Conv2d(96, 256, kernel_size=5, padding=2),\n", + " nn.ReLU(inplace=True),\n", + " nn.MaxPool2d(kernel_size=3, stride=2),\n", + " nn.LocalResponseNorm(5, alpha=0.0001, beta=0.75),\n", + " nn.Conv2d(256, 256, kernel_size=3, padding=1),\n", + " nn.ReLU(inplace=True),\n", + " nn.MaxPool2d(kernel_size=3, stride=2),\n", + " )\n", + " self.regression = nn.Sequential(\n", + " nn.Linear(256*5*7, 4096),\n", + " nn.ReLU(inplace=True),\n", + " nn.Dropout(),\n", + " nn.Linear(4096, 256),\n", + " nn.ReLU(inplace=True),\n", + " nn.Dropout(),\n", + " nn.Linear(256, output)\n", + " )\n", + "\n", + " def forward(self, x):\n", + " x = self.features(x)\n", + " x = x.view(x.size(0), 256 * 35)\n", + " x = self.regression(x)\n", + " return x" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "----------------------------------------------------------------\n", + " Layer (type) Output Shape Param #\n", + "================================================================\n", + " Conv2d-1 [-1, 96, 51, 69] 34,944\n", + " ReLU-2 [-1, 96, 51, 69] 0\n", + " MaxPool2d-3 [-1, 96, 25, 34] 0\n", + " LocalResponseNorm-4 [-1, 96, 25, 34] 0\n", + " Conv2d-5 [-1, 256, 25, 34] 614,656\n", + " ReLU-6 [-1, 256, 25, 34] 0\n", + " MaxPool2d-7 [-1, 256, 12, 16] 0\n", + " LocalResponseNorm-8 [-1, 256, 12, 16] 0\n", + " Conv2d-9 [-1, 256, 12, 16] 590,080\n", + " ReLU-10 [-1, 256, 12, 16] 0\n", + " MaxPool2d-11 [-1, 256, 5, 7] 0\n", + " Linear-12 [-1, 4096] 36,704,256\n", + " ReLU-13 [-1, 4096] 0\n", + " Dropout-14 [-1, 4096] 0\n", + " Linear-15 [-1, 256] 1,048,832\n", + " ReLU-16 [-1, 256] 0\n", + " Dropout-17 [-1, 256] 0\n", + " Linear-18 [-1, 9] 2,313\n", + "================================================================\n", + "Total params: 38,995,081\n", + "Trainable params: 38,995,081\n", + "Non-trainable params: 0\n", + "----------------------------------------------------------------\n", + "Input size (MB): 0.67\n", + "Forward/backward pass size (MB): 11.39\n", + "Params size (MB): 148.75\n", + "Estimated Total Size (MB): 160.82\n", + "----------------------------------------------------------------\n" + ] + } + ], + "source": [ + "net = DDAlexNet(len(valid)).cuda()\n", + "criterion = nn.MSELoss(reduction='mean')\n", + "optimizer = optim.Adam(net.parameters(),lr=0.01)\n", + "\n", + "train_writer = tbx.SummaryWriter('./log/train')\n", + "valid_writer = tbx.SummaryWriter('./log/valid')\n", + "\n", + "# Enable to see model\n", + "summary(net, (3, 210, 280))" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "DDAlexNet(\n", + " (features): Sequential(\n", + " (0): Conv2d(3, 96, kernel_size=(11, 11), stride=(4, 4), padding=(2, 2))\n", + " (1): ReLU(inplace=True)\n", + " (2): MaxPool2d(kernel_size=3, stride=2, padding=0, dilation=1, ceil_mode=False)\n", + " (3): LocalResponseNorm(5, alpha=0.0001, beta=0.75, k=1.0)\n", + " (4): Conv2d(96, 256, kernel_size=(5, 5), stride=(1, 1), padding=(2, 2))\n", + " (5): ReLU(inplace=True)\n", + " (6): MaxPool2d(kernel_size=3, stride=2, padding=0, dilation=1, ceil_mode=False)\n", + " (7): LocalResponseNorm(5, alpha=0.0001, beta=0.75, k=1.0)\n", + " (8): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n", + " (9): ReLU(inplace=True)\n", + " (10): MaxPool2d(kernel_size=3, stride=2, padding=0, dilation=1, ceil_mode=False)\n", + " )\n", + " (regression): Sequential(\n", + " (0): Linear(in_features=8960, out_features=4096, bias=True)\n", + " (1): ReLU(inplace=True)\n", + " (2): Dropout(p=0.5, inplace=False)\n", + " (3): Linear(in_features=4096, out_features=256, bias=True)\n", + " (4): ReLU(inplace=True)\n", + " (5): Dropout(p=0.5, inplace=False)\n", + " (6): Linear(in_features=256, out_features=9, bias=True)\n", + " )\n", + ")" + ] + }, + "execution_count": 14, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "def init_normal(m):\n", + " if type(m) == nn.Linear:\n", + " nn.init.uniform_(m.weight)\n", + "net.apply(init_normal)" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [ + { + "ename": "KeyboardInterrupt", + "evalue": "", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mKeyboardInterrupt\u001b[0m Traceback (most recent call last)", + "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[1;32m 5\u001b[0m \u001b[0mvalid_num\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;36m0\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 6\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 7\u001b[0;31m \u001b[0;32mfor\u001b[0m \u001b[0mi\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtrain_sample\u001b[0m \u001b[0;32min\u001b[0m \u001b[0menumerate\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtrain_dataloader\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 8\u001b[0m \u001b[0mtrain_inputs\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mtrain_sample\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'image'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcuda\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 9\u001b[0m \u001b[0mtrain_target\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mtrain_sample\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'affordance_vector'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcuda\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;32m~/anaconda3/envs/torch/lib/python3.6/site-packages/torch/utils/data/dataloader.py\u001b[0m in \u001b[0;36m__next__\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 802\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 803\u001b[0m \u001b[0;32massert\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_shutdown\u001b[0m \u001b[0;32mand\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_tasks_outstanding\u001b[0m \u001b[0;34m>\u001b[0m \u001b[0;36m0\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 804\u001b[0;31m \u001b[0midx\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdata\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_get_data\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 805\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_tasks_outstanding\u001b[0m \u001b[0;34m-=\u001b[0m \u001b[0;36m1\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 806\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;32m~/anaconda3/envs/torch/lib/python3.6/site-packages/torch/utils/data/dataloader.py\u001b[0m in \u001b[0;36m_get_data\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 759\u001b[0m \u001b[0;32melif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_pin_memory\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 760\u001b[0m \u001b[0;32mwhile\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_pin_memory_thread\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mis_alive\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 761\u001b[0;31m \u001b[0msuccess\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdata\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_try_get_data\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 762\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0msuccess\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 763\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mdata\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;32m~/anaconda3/envs/torch/lib/python3.6/site-packages/torch/utils/data/dataloader.py\u001b[0m in \u001b[0;36m_try_get_data\u001b[0;34m(self, timeout)\u001b[0m\n\u001b[1;32m 722\u001b[0m \u001b[0;31m# (bool: whether successfully get data, any: data if successful else None)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 723\u001b[0m \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 724\u001b[0;31m \u001b[0mdata\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_data_queue\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtimeout\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mtimeout\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 725\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdata\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 726\u001b[0m \u001b[0;32mexcept\u001b[0m \u001b[0mException\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0me\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;32m~/anaconda3/envs/torch/lib/python3.6/queue.py\u001b[0m in \u001b[0;36mget\u001b[0;34m(self, block, timeout)\u001b[0m\n\u001b[1;32m 171\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mremaining\u001b[0m \u001b[0;34m<=\u001b[0m \u001b[0;36m0.0\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 172\u001b[0m \u001b[0;32mraise\u001b[0m \u001b[0mEmpty\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 173\u001b[0;31m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mnot_empty\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mwait\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mremaining\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 174\u001b[0m \u001b[0mitem\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_get\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 175\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mnot_full\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mnotify\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;32m~/anaconda3/envs/torch/lib/python3.6/threading.py\u001b[0m in \u001b[0;36mwait\u001b[0;34m(self, timeout)\u001b[0m\n\u001b[1;32m 297\u001b[0m \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 298\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mtimeout\u001b[0m \u001b[0;34m>\u001b[0m \u001b[0;36m0\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 299\u001b[0;31m \u001b[0mgotit\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mwaiter\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0macquire\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtimeout\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 300\u001b[0m \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 301\u001b[0m \u001b[0mgotit\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mwaiter\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0macquire\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;32mFalse\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;31mKeyboardInterrupt\u001b[0m: " + ] + } + ], + "source": [ + "for epoch in range(20):\n", + " train_loss_tot = 0\n", + " train_num = 0 \n", + " valid_loss_tot = 0\n", + " valid_num = 0\n", + "\n", + " for i, train_sample in enumerate(train_dataloader):\n", + " train_inputs = train_sample['image'].cuda()\n", + " train_target = train_sample['affordance_vector'].cuda()\n", + "\n", + " train_outputs = net(train_inputs)\n", + " #print(train_inputs.cpu())\n", + " #print('target:{}'.format(train_sample['affordance_vector'][0]))\n", + " #print('outputs:{}'.format(train_outputs.cpu()[0]))\n", + " train_loss = criterion(train_outputs, train_target)\n", + "\n", + " optimizer.zero_grad()\n", + " train_loss.backward()\n", + " optimizer.step()\n", + " #logging.info(\"Epoch:{}, Sample:{}, Training Loss:{}\".format(epoch,i,train_loss))\n", + " train_loss_tot += train_loss\n", + " train_num += train_inputs.size(0)\n", + " #train_writer.add_scalar('Loss', train_loss.item(), epoch)\n", + "\n", + " with torch.no_grad():\n", + " for i, valid_sample in enumerate(validation_dataloader):\n", + " valid_inputs = valid_sample['image'].cuda()\n", + " valid_target = valid_sample['affordance_vector'].cuda()\n", + " valid_outputs = net(valid_inputs)\n", + " valid_loss = criterion(valid_outputs,valid_target)\n", + " #logging.info(\"Epoch:{}, Sample:{}, Validating Loss:{}\".format(epoch,i,valid_loss))\n", + " valid_loss_tot += valid_loss\n", + " valid_num += valid_inputs.size(0)\n", + " #valid_writer.add_scalar('Loss', valid_loss.item(), epoch)\n", + "\n", + " logging.info(\"Epoch:{}, Training Samples:{}, Training Loss:{}\".format(epoch,train_num,train_loss_tot/train_num))\n", + " logging.info(\"Epoch:{}, Validating Samples:{}, Validating Loss:{}\".format(epoch,valid_num,valid_loss_tot/valid_num))\n", + " train_writer.add_scalar('Loss', train_loss_tot/train_num, epoch)\n", + " valid_writer.add_scalar('Loss', valid_loss_tot/valid_num, epoch)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.6.7" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/avs_debug.py b/src/data/avs_debug.py similarity index 100% rename from avs_debug.py rename to src/data/avs_debug.py diff --git a/avs_reporter.py b/src/data/avs_reporter.py similarity index 100% rename from avs_reporter.py rename to src/data/avs_reporter.py diff --git a/generate_data.py b/src/data/generate_data.py similarity index 94% rename from generate_data.py rename to src/data/generate_data.py index 91d81ec..847064b 100755 --- a/generate_data.py +++ b/src/data/generate_data.py @@ -3,6 +3,16 @@ import os import sys import shutil +import glob + +try: + sys.path.append(glob.glob('CARLA_0.9.5/PythonAPI/carla/dist/carla-*%d.%d-%s.egg' % ( + sys.version_info.major, + sys.version_info.minor, + 'win-amd64' if os.name == 'nt' else 'linux-x86_64'))[0]) +except IndexError: + pass + import carla import random import time @@ -54,7 +64,7 @@ CAM_ROT = (args['cam_yaw'],args['cam_pitch'],args['cam_roll']) FPS = 10 INTERVAL = 1/FPS -NAME = "{}-{}".format(args['name'],MAX_TIME) +NAME = "{}".format(args['name']) CSV_NAME = "{}_labels.csv".format(NAME) MAXD = args['max_dist'] DEBUG = args['debug'] @@ -91,6 +101,7 @@ def main(): hero += 1 vx = None for a in world.get_actors(): + print(a.type_id,EGO_TYPE) if EGO_TYPE in a.type_id: vx = a actor_list.append(vx) @@ -157,7 +168,7 @@ def main(): avs = avss[1] avs = [x if x != None else -1 for x in avs] # e.g. v1-frame# - avs.insert(0,"v{}-{}".format(i,timestamp.frame_count)) + avs.insert(0,"{}-v{}-{}".format(NAME,i,timestamp.frame_count)) # Filter out entiries that are (not on highway|front cars too far away) lanes = avs[-1] @@ -194,10 +205,10 @@ def main(): settings.synchronous_mode = False world.apply_settings(settings) csvfile.close() - if not os.path.exists('./output'): - os.mkdir('./output') - shutil.move("./{}".format(NAME),"./output") - shutil.move("./{}".format(CSV_NAME),"./output") + if not os.path.exists('../../data'): + os.mkdir('../../data') + shutil.move("./{}".format(NAME),"../../data") + shutil.move("./{}".format(CSV_NAME),"../../data/{}".format(NAME)) print('done.') diff --git a/manual_control.py b/src/data/manual_control.py similarity index 99% rename from manual_control.py rename to src/data/manual_control.py index 480e9e8..3d575b8 100755 --- a/manual_control.py +++ b/src/data/manual_control.py @@ -56,7 +56,7 @@ try: - sys.path.append(glob.glob('../carla/dist/carla-*%d.%d-%s.egg' % ( + sys.path.append(glob.glob('CARLA_0.9.5/PythonAPI/carla/dist/carla-*%d.%d-%s.egg' % ( sys.version_info.major, sys.version_info.minor, 'win-amd64' if os.name == 'nt' else 'linux-x86_64'))[0]) diff --git a/src/data/merge.sh b/src/data/merge.sh new file mode 100755 index 0000000..3f10be1 --- /dev/null +++ b/src/data/merge.sh @@ -0,0 +1,22 @@ +#!/bin/bash + + +while [[ "$#" -gt 0 ]]; do case $1 in + -r|--remove-files) remove=1; shift;; + -v|--verbose) verbose=1;; + *) echo "Unknown parameter passed: $1"; exit 1;; +esac; shift; done + +cat ../../data/*/*.csv > ../../data/all.csv + +if [ "$verbose" = "1" ] +then + read lines words chars <<< $(wc ../../data/all.csv) + echo "Done!" + echo "Total number of samples: $lines" +fi + +if [ "$remove" = "1" ] +then + rm ../../data/*/*.csv +fi diff --git a/src/models/dataset.py b/src/models/dataset.py new file mode 100755 index 0000000..6e9b264 --- /dev/null +++ b/src/models/dataset.py @@ -0,0 +1,94 @@ +import sys +import os +import numpy as np +from pandas import read_csv +from skimage import io, transform +from torch.utils.data import Dataset + +value_range = [ + (-0.5, 0.5), # angle + (-7, -2.5), # toMarking_L + (-2, 3.5), # toMarking_M + ( 2.5, 7), # toMarking_R + ( 0, 75), # dist_L + ( 0, 75), # dist_R + (-9.5, -4), # toMarking_LL + (-5.5, -0.5), # toMarking_ML + ( 0.5, 5.5), # toMarking_MR + ( 4, 9.5), # toMarking_RR + ( 0, 75), # dist_LL + ( 0, 75), # dist_MM + ( 0, 75), # dist_RR + ( 0, 1) # fast +] + +min_nv = 0.1 +max_nv = 0.9 + +def normalize(av): + def f(v, r): + v = float(v) + min_v = float(r[0]) + max_v = float(r[1]) + v = (v - min_v) / (max_v - min_v) + v = v * (max_nv - min_nv) + min_nv + v = min(max(v, 0.0), 1.0) + return v + + for (i, v) in enumerate(av): + av[i] = f(v, value_range[i]) + + return av + +def denormalize(av): + def f(v, r): + v = float(v) + min_v = float(r[0]) + max_v = float(r[1]) + v = (v - min_nv) / (max_nv - min_nv) + v = v * (max_v - min_v) + min_v + return v + + for (i, v) in enumerate(av): + av[i] = f(v, value_range[i]) + + return av + +class CarlaDataset(Dataset): + """CARLA dataset.""" + + def __init__(self, csv_file, root_dir, valid, transform=None): + self.metadata = read_csv(csv_file, header=None) + self.root_dir = root_dir + self.transform = transform + self.valid = valid + + def __len__(self): + return len(self.metadata) + + def __getitem__(self, idx): + img_id = self.metadata.iloc[idx,0].split('-') + img_name = os.path.join(self.root_dir, img_id[0], img_id[1], "{}.png".format(img_id[2])) + image = io.imread(img_name) + + # Delete alpha channel + if image.shape[-1] == 4: + image = np.delete(image, 3, 2) + + # Scale to 280x210 + image = transform.resize(image, (210, 280, 3), mode='constant', anti_aliasing=True) + + # Make it CHW + image = image.transpose(2, 0, 1).astype('float32') + + av = self.metadata.iloc[idx,1:].values + av = av.astype('float32') + av = av[self.valid] + av = normalize(av) + sample = {'image': image, 'affordance_vector': av} + + if self.transform: + sample = self.transform(sample) + + return sample + diff --git a/src/models/deep_driving.py b/src/models/deep_driving.py new file mode 100755 index 0000000..5d327b1 --- /dev/null +++ b/src/models/deep_driving.py @@ -0,0 +1,106 @@ +import torch.nn as nn +import torch.nn.init as init +import torchvision.models.squeezenet as sqn + +__all__ = ['deep_driving'] + +class DDAlexNet(nn.Module): + + def __init__(self, output): + super(DDAlexNet, self).__init__() + self.features = nn.Sequential( + nn.Conv2d(3, 96, kernel_size=11, stride=4, padding=2), + nn.ReLU(inplace=True), + nn.MaxPool2d(kernel_size=3, stride=2), + nn.LocalResponseNorm(5, alpha=0.0001, beta=0.75), + nn.Conv2d(96, 256, kernel_size=5, padding=2), + nn.ReLU(inplace=True), + nn.MaxPool2d(kernel_size=3, stride=2), + nn.LocalResponseNorm(5, alpha=0.0001, beta=0.75), + nn.Conv2d(256, 384, kernel_size=3, padding=1), + nn.ReLU(inplace=True), + nn.Conv2d(384, 256, kernel_size=3, padding=1), + nn.ReLU(inplace=True), + nn.Conv2d(256, 256, kernel_size=3, padding=1), + nn.ReLU(inplace=True), + nn.MaxPool2d(kernel_size=3, stride=2), + ) + self.regression = nn.Sequential( + nn.Linear(256*5*7, 4096), + nn.ReLU(inplace=True), + nn.Dropout(), + nn.Linear(4096, 4096), + nn.ReLU(inplace=True), + nn.Dropout(), + nn.Linear(4096, 256), + nn.ReLU(inplace=True), + nn.Dropout(), + nn.Linear(256, output), + nn.Sigmoid() + ) + + def forward(self, x): + x = self.features(x) + x = x.view(x.size(0), 256 * 35) + x = self.regression(x) + return x + +class DDSqueezeNet(nn.Module): + def __init__(self, output): + super(DDSqueezeNet, self).__init__() + self.features = nn.Sequential( + nn.Conv2d(3, 64, kernel_size=3, stride=2), + nn.ReLU(inplace=True), + nn.MaxPool2d(kernel_size=3, stride=2, ceil_mode=False), + sqn.Fire(64, 16, 64, 64), + sqn.Fire(128, 16, 64, 64), + nn.MaxPool2d(kernel_size=3, stride=2, ceil_mode=False), + sqn.Fire(128, 32, 128, 128), + sqn.Fire(256, 32, 128, 128), + nn.MaxPool2d(kernel_size=3, stride=2, ceil_mode=False), + sqn.Fire(256, 48, 192, 192), + sqn.Fire(384, 48, 192, 192), + sqn.Fire(384, 64, 256, 256), + sqn.Fire(512, 64, 256, 256), + ) + # Final convolution is initialized differently form the rest + final_conv = nn.Conv2d(512, 256, kernel_size=1) + self.regression1 = nn.Sequential( + nn.Dropout(p=0.5), + final_conv, + nn.ReLU(inplace=True), + nn.AdaptiveAvgPool2d((1, 1)), + ) + + self.regression2 = nn.Sequential( + nn.Linear(256, output), + nn.Sigmoid(), + ) + + for m in self.modules(): + if isinstance(m, nn.Conv2d): + if m is final_conv: + init.normal_(m.weight, mean=0.0, std=0.01) + else: + init.kaiming_uniform_(m.weight) + if m.bias is not None: + init.constant_(m.bias, 0) + + def forward(self, x): + x = self.features(x) + x = self.regression1(x) + x = x.view(x.size(0), 256) + x = self.regression2(x) + return x + + + +def deep_driving(idx,output,**kwargs): + r"""DeepDirving model + """ + #model = DDAlexNet(**kwargs) + if idx == 'alex': + model = DDAlexNet(output,**kwargs) + elif idx == 'squeeze': + model = DDSqueezeNet(output,**kwargs) + return model diff --git a/src/models/trainer.py b/src/models/trainer.py new file mode 100755 index 0000000..ce30ba7 --- /dev/null +++ b/src/models/trainer.py @@ -0,0 +1,140 @@ +import sys +import shutil +import os.path as path +import os +import torch +import torch.nn as nn +import torch.onnx as onnx +import torch.optim as optim +from torch.utils.data import DataLoader +from torchsummary import summary +import dataset as ds +import deep_driving as dd +import tensorboardX as tbx +import argparse +import numpy as np +from torch.utils.data.sampler import SubsetRandomSampler +import logging +import glob + +# torch.set_default_tensor_type('torch.cuda.FloatTensor') +parser = argparse.ArgumentParser(description='Training NN') +parser.add_argument('--root-dir','-rd',metavar='str', help='Root directory of the data',type=str,required=True) +parser.add_argument('--csv-name','-cn',metavar='str', help='CSV label file name',type=str,required=True) +parser.add_argument('--learning-rate','-lr',metavar='float', help='Learning rate',type=float,default=0.01) +parser.add_argument('--nn-name','-nn',metavar='str', help='Alex or Squeeze',type=str,default='alex') +args = vars(parser.parse_args()) + +if not os.path.exists('./log'): + os.mkdir('./log') +logging.basicConfig(level=logging.INFO, + format='%(asctime)s %(name)-12s %(levelname)-8s %(message)s', + datefmt='%m-%d %H:%M', + filename='./log/log.txt', + filemode='w') +console = logging.StreamHandler() +console.setLevel(logging.INFO) +formatter = logging.Formatter('%(name)-12s: %(levelname)-8s %(message)s') +console.setFormatter(formatter) +logging.getLogger('').addHandler(console) + +valid = [0] + [i for i in range(6,14)] +net = dd.deep_driving(args['nn_name'],output=len(valid)).cuda() +criterion = nn.MSELoss(reduction='mean') +optimizer = optim.Adam(net.parameters(),lr=0.01) + +train_writer = tbx.SummaryWriter('./log/train') +valid_writer = tbx.SummaryWriter('./log/valid') + +# Enable to see model +summary(net, (3, 210, 280)) + +validation_split = .2 +random_seed= 25 +carla_dataset = ds.CarlaDataset(csv_file=path.join(args['root_dir'], args['csv_name']), + root_dir=args['root_dir'], valid=valid) +dataset_size = len(carla_dataset) +indices = list(range(dataset_size)) +split = int(np.floor(validation_split * dataset_size)) +np.random.seed(random_seed) +np.random.shuffle(indices) +train_indices, val_indices = indices[split:], indices[:split] + +# Creating PT data samplers and loaders: +train_sampler = SubsetRandomSampler(train_indices) +valid_sampler = SubsetRandomSampler(val_indices) + +train_dataloader = DataLoader(carla_dataset, batch_size=64, num_workers=16, pin_memory=True, sampler=train_sampler) +validation_dataloader = DataLoader(carla_dataset, batch_size=64, num_workers=16, pin_memory=True, sampler=valid_sampler) + +def init_normal(m): + if type(m) == nn.Linear: + nn.init.uniform_(m.weight) +net.apply(init_normal) + +for epoch in range(20): + train_loss_tot = 0 + train_num = 0 + valid_loss_tot = 0 + valid_num = 0 + + for i, train_sample in enumerate(train_dataloader): + train_inputs = train_sample['image'].cuda() + train_target = train_sample['affordance_vector'].cuda() + + train_outputs = net(train_inputs) + #print(train_inputs.cpu()) + print('target:{}'.format(train_sample['affordance_vector'][0])) + print('outputs:{}'.format(train_outputs.cpu()[0])) + train_loss = criterion(train_outputs, train_target) + + optimizer.zero_grad() + train_loss.backward() + optimizer.step() + logging.info("Epoch:{}, Sample:{}, Training Loss:{}".format(epoch,i,train_loss)) + train_loss_tot += train_loss + train_num += train_inputs.size(0) + #train_writer.add_scalar('Loss', train_loss.item(), epoch) + + with torch.no_grad(): + for i, valid_sample in enumerate(validation_dataloader): + valid_inputs = valid_sample['image'].cuda() + valid_target = valid_sample['affordance_vector'].cuda() + valid_outputs = net(valid_inputs) + valid_loss = criterion(valid_outputs,valid_target) + logging.info("Epoch:{}, Sample:{}, Validating Loss:{}".format(epoch,i,valid_loss)) + valid_loss_tot += valid_loss + valid_num += valid_inputs.size(0) + #valid_writer.add_scalar('Loss', valid_loss.item(), epoch) + + logging.info("Epoch:{}, Training Samples:{}, Training Loss:{}".format(epoch,train_num,train_loss_tot/train_num)) + logging.info("Epoch:{}, Validating Samples:{}, Validating Loss:{}".format(epoch,valid_num,valid_loss_tot/valid_num)) + train_writer.add_scalar('Loss', train_loss_tot/train_num, epoch) + valid_writer.add_scalar('Loss', valid_loss_tot/valid_num, epoch) + + #print('[%d/30, %5d/%5d] Training Loss: %.3f Validating Loss: %.3f' % (epoch, i, len(dataloader), train_loss.item(),valid_loss.item())) + + +torch.save(net.state_dict(), './dd_{}'.format(args['nn_name'])) + +train_writer.export_scalars_to_json('./train.json') +train_writer.close() +valid_writer.export_scalars_to_json('./valid.json') +valid_writer.close() + +if not path.exists('./runs'): + os.mkdir('./runs') +if not path.exists('./runs/train'): + shutil.move('./train','./runs') + shutil.move('./valid','./runs') +else: + for file in glob.glob(r'./train/*'): + shutil.move(file,'./runs/train') + os.rmdir('./train') + for file in glob.glob(r'./valid/*'): + shutil.move(file,'./runs/valid') + os.rmdir('./valid') + +onnx._export(net.cpu(), torch.randn(1, 3, 210, 280), "dd_{}.onnx".format(args['nn_name']), export_params=True) + +logging.info(print('Finished Training'))