clean up

gist1/gpt.py

@@ -7,12 +7,9 @@
 import torch
 import torch.nn as nn
 import torch.nn.functional as F
-from torch.optim import Optimizer
 from torch.optim.lr_scheduler import _LRScheduler
 import numpy as np
 
-import time
-
 import copy
 
 def new_gelu(x):

gist1/vqvae_gpt.py

@@ -4,9 +4,7 @@ import torch.nn.functional as F
 from gist1.gpt import GPT
 from gist1.vqvae import VQVAE
 
-from utils.misc import save_params, load_params
-import os
-import time
+from utils.misc import load_params
 
 
 class VQVAETransformer(nn.Module):
@@ -44,11 +42,6 @@ class VQVAETransformer(nn.Module):
 
         return model
 
-    def load_vqvae_weight(self, args):
-        VQVAE_path = args['vqvae_checkpoint']
-        self.vqvae.load_state_dict(torch.load(VQVAE_path))
-        self.vqvae.eval()
-
     def load_transformer(self, args):
         # seed= args['seed']
         # torch.manual_seed(seed)

utils/isoutil.py

@@ -4,24 +4,11 @@ from matplotlib.patches import Polygon
 from matplotlib.collections import PatchCollection
 
 
-
 def pol2car(rho, pi, xi, yi):
     x = rho * np.cos(pi) + xi
     y = rho * np.sin(pi) + yi
     return (x, y)
 
-def car2pol(xi, yi):
-    rho = np.sqrt(xi**2 + yi**2)
-    phi = np.arctan2(yi, xi)
-    return (rho, phi)
-
-def car2polnorm(xi, yi):
-    rho = np.sqrt(xi**2 + yi**2)
-    phi = np.arctan2(yi, xi)
-    phi %= 2*np.pi
-    phi /= 2*np.pi
-    return (rho, phi)
-
 def plot_isovist(isovists, show_axis=False, s=0.1, figsize=(5,5)):
     #transpose the matrix
     # isovists = np.transpose(isovists, (isovists.ndim-1, isovists.ndim-2))
@@ -45,74 +32,6 @@ def plot_isovist(isovists, show_axis=False, s=0.1, figsize=(5,5)):
     ax.scatter(x, y, s, 'black')
     return fig
 
-from matplotlib.backends.backend_agg import FigureCanvasAgg as FigureCanvas
-from matplotlib.figure import Figure
-
-
-def isovist_to_img(isovist, show_axis=False, s=0.1, figsize=(5,5)):
-    points = []
-    xy = (0, 0)
-    res = np.pi/90
-    isovist = isovist + 0.5
-    for j, rho in enumerate(isovist):
-            if rho <= 2.0:
-                pt = pol2car(rho, j*res, xy[0], xy[1])
-                points.append(pt)
-    x = [i[0] for i in points]
-    y = [i[1] for i in points]
-    fig = plt.figure(figsize=figsize)
-    canvas = FigureCanvas(fig)
-    ax = fig.add_subplot(111)
-    ax.set_aspect('equal')
-    ax.set_xlim(-1,1)
-    ax.set_ylim(-1,1)
-    if not show_axis:
-        ax.axis('off')
-    ax.scatter(x, y, s, 'black')
-
-    canvas.draw()
-    image = np.fromstring(canvas.tostring_rgb(), dtype='uint8')
-    return image
-
-def isovist_to_img_a(isovist, show_axis=False, s=0.1, figsize=(5,5)):
-    points = []
-    xy = (0, 0)
-    res = np.pi/128
-    isovist = isovist + 0.5
-    for j, rho in enumerate(isovist):
-            if rho <= 2.0:
-                pt = pol2car(rho, j*res, xy[0], xy[1])
-                points.append(pt)
-    x = [i[0] for i in points]
-    y = [i[1] for i in points]
-    fig = plt.figure(figsize=figsize)
-    canvas = FigureCanvas(fig)
-    ax = fig.add_subplot(111)
-    ax.set_aspect('equal')
-    ax.set_xlim(-1,1)
-    ax.set_ylim(-1,1)
-    if not show_axis:
-        ax.axis('off')
-    ax.scatter(x, y, s, 'black')
-
-    canvas.draw()
-    image = np.fromstring(canvas.tostring_rgb(), dtype='uint8')
-    return image
-
-def isovist_to_cartesian(isovist, x, y, scale):
-    points = []
-    xy = (x, y)
-    res = np.pi/90
-    isovist = isovist * scale
-    for j, rho in enumerate(isovist):
-        if rho <= scale:
-            pt = pol2car(rho, j*res, xy[0], xy[1])
-            points.append(pt)
-        else:
-            pt = pol2car(scale, j*res, xy[0], xy[1])
-            points.append(pt)
-    points = np.stack(points)
-    return(points)
 
 def isovist_to_cartesian_a(isovist, x, y, scale):
     points = []
@@ -125,49 +44,6 @@ def isovist_to_cartesian_a(isovist, x, y, scale):
     points = np.stack(points)
     return(points)
 
-def isovist_to_cartesian_b(isovist, x, y):
-    points = []
-    xy = (x, y)
-    res = np.pi*2
-    isovist = isovist
-    for j, rho in isovist:
-        pt = pol2car(rho, j*res, xy[0], xy[1])
-        points.append(pt)
-    points = np.stack(points)
-    return(points)
-
-def isovist_to_cartesian_segment(isovist, x, y, scale):
-    points = []
-    segment = []
-    xy = (x, y)
-    res = np.pi/90
-    isovist = isovist * scale
-    p_rho = isovist[-1]
-    for j, rho in enumerate(isovist):
-        delta = abs(p_rho-rho)
-        if j == 0:
-            first_rho = rho
-        if rho < 0.98 * scale and delta < 0.05 * scale:
-            pt = pol2car(rho, j*res, xy[0], xy[1])
-            segment.append(pt)
-        else:
-            points.append(segment)
-            segment = []
-        p_rho = rho
-    if first_rho < 1.0 * scale and abs(rho-first_rho)< 0.05 * scale :
-        if len(points) > 0:
-            segment.extend(points[0])
-            points[0]=segment
-        else:
-            points.append(segment)
-    else:
-        points.append(segment)
-    segments = []
-    for i in range(len(points)):
-        if len(points[i])>0:
-            segment = np.stack(points[i])
-            segments.append(segment)
-    return(segments)
 
 def isovist_to_cartesian_segment_a(isovist, x, y, scale, max=0.98, min = 0.1, d=0.1):
     points = []
@@ -203,301 +79,6 @@ def isovist_to_cartesian_segment_a(isovist, x, y, scale, max=0.98, min = 0.1, d=
     return(segments)
 
 
-def isovist_to_cartesian_segment_b(isovist, x, y):
-    points = []
-    segment = []
-    xy = (x, y)
-    res = np.pi*2
-    isovist = isovist
-    p_rho = isovist[-1, 1]
-    _i = 0
-    for j, rho in isovist:
-        delta = abs(p_rho-rho)
-        if _i == 0:
-            first_rho = rho
-        if rho < 0.98 and delta < 0.1 :
-            pt = pol2car(rho, j*res, xy[0], xy[1])
-            segment.append(pt)
-        else:
-            points.append(segment)
-            segment = []
-        p_rho = rho
-        _i += 1
-    if first_rho < 0.98  and abs(rho-first_rho)< 0.1:
-        if len(points) > 0:
-            segment.extend(points[0])
-            points[0]=segment
-        else:
-            points.append(segment)
-    else:
-        points.append(segment)
-    segments = []
-    for i in range(len(points)):
-        if len(points[i])>0:
-            segment = np.stack(points[i])
-            segments.append(segment)
-    return(segments)
-
-
-# plotting an isovist and return the numpy image
-def plot_isovist_numpy(k, text=None, figsize=(8,8)):
-    fig, ax = plt.subplots(1,1, figsize=figsize, dpi=300)
-
-    #plot isovist
-    xy = isovist_to_cartesian_a(k, 0, 0, 1.0)
-    polygon = Polygon(xy, True)
-    p = PatchCollection([polygon])
-    p.set_facecolor('#dddddd')
-    p.set_edgecolor(None)
-    ax.add_collection(p)
-
-    # style
-    ax.set_aspect('equal')
-    lim = 1.2
-    ax.set_xlim(-lim,lim)
-    ax.set_ylim(-lim,lim)
-    ax.set_xticks([])
-    ax.set_yticks([])
-    ax.axis('off')
-    if text != None:
-        ax.set_title(text, size=5) # Title
-        fig.tight_layout()
-
-    # for plot with torchvision util
-    fig.canvas.draw()
-    data = np.frombuffer(fig.canvas.tostring_rgb(), dtype=np.uint8)
-    w, h = fig.canvas.get_width_height()
-    im = data.reshape((int(h), int(w), -1))
-    im = im.transpose((2, 0, 1))
-    plt.close()
-    return im
-
-
-
-# plotting isovist and boundary from  and return the numpy image
-def plot_isovist_boundary_numpy(isovist, boundary, figsize=(8,8)):
-    fig, ax = plt.subplots(1,1, figsize=figsize, dpi=300)
-
-    #plot isovist
-    xy = isovist_to_cartesian_a(isovist, 0, 0, 1.0)
-    polygon = Polygon(xy, True)
-    p = PatchCollection([polygon])
-    p.set_facecolor('#eeeeee')
-    p.set_edgecolor(None)
-    ax.add_collection(p)
-
-
-    #plot assumed boundary
-    edge_patches = []
-    segments = isovist_to_cartesian_segment_a(boundary, 0, 0, 1.0)
-    for segment in segments:
-        polygon = Polygon(segment, False)
-        edge_patches.append(polygon)
-    p = PatchCollection(edge_patches)
-    p.set_facecolor('none')
-    p.set_edgecolor('#000000')
-    p.set_linewidth(0.5)
-    ax.add_collection(p)
-
-    # style
-    ax.set_aspect('equal')
-    lim = 1.2
-    ax.set_xlim(-lim,lim)
-    ax.set_ylim(-lim,lim)
-    ax.set_xticks([])
-    ax.set_yticks([])
-    ax.axis('off')
-
-    # for plot with torchvision util
-    fig.canvas.draw()
-    data = np.frombuffer(fig.canvas.tostring_rgb(), dtype=np.uint8)
-    w, h = fig.canvas.get_width_height()
-    im = data.reshape((int(h), int(w), -1))
-    im = im.transpose((2, 0, 1))
-    plt.close()
-    return im
-
-
-# plotting two isovists (fill and edge) and return the numpy image
-def plot_isovist_double_numpy(isovist1, isovist2, figsize=(8,8)):
-    fig, ax = plt.subplots(1,1, figsize=figsize, dpi=300)
-
-    #plot isovist1
-    xy = isovist_to_cartesian_a(isovist1, 0, 0, 1.0)
-    polygon = Polygon(xy, True)
-    p = PatchCollection([polygon])
-    p.set_facecolor('#dddddd')
-    p.set_edgecolor(None)
-    ax.add_collection(p)
-
-    #plot isovist2 as boundary
-    xy = isovist_to_cartesian_a(isovist2, 0, 0, 1.0)
-    polygon = Polygon(xy, True)
-    p = PatchCollection([polygon])
-    p.set_facecolor('none')
-    p.set_edgecolor('#000000')
-    p.set_linewidth(0.2)
-    ax.add_collection(p)
-
-    # style
-    ax.set_aspect('equal')
-    lim = 1.2
-    ax.set_xlim(-lim,lim)
-    ax.set_ylim(-lim,lim)
-    ax.set_xticks([])
-    ax.set_yticks([])
-    ax.axis('off')
-
-    # for plot with torchvision util
-    fig.canvas.draw()
-    data = np.frombuffer(fig.canvas.tostring_rgb(), dtype=np.uint8)
-    w, h = fig.canvas.get_width_height()
-    im = data.reshape((int(h), int(w), -1))
-    im = im.transpose((2, 0, 1))
-    plt.close()
-    return im
-
-
-# plotting two isovists (fill and edge) and return the numpy image
-def plot_isovist_triple_numpy(isovists, locs, figsize=(8,8)):
-    isovist1, isovist2, isovist3 = isovists
-    loc1, loc2, loc3 = locs
-
-    fig, ax = plt.subplots(1,1, figsize=figsize, dpi=300)
-
-    #plot isovist1
-    xy = isovist_to_cartesian_a(isovist1, loc1[0], loc1[1], 1.0)
-    polygon = Polygon(xy, True)
-    p = PatchCollection([polygon])
-    p.set_facecolor('#ffdddd')
-    p.set_edgecolor(None)
-    ax.add_collection(p)
-
-    #plot isovist2
-    xy = isovist_to_cartesian_a(isovist2, loc2[0], loc2[1], 1.0)
-    polygon = Polygon(xy, True)
-    p = PatchCollection([polygon])
-    p.set_facecolor('#ddddff')
-    p.set_edgecolor(None)
-    ax.add_collection(p)
-
-    #plot isovist3 as boundary
-    xy = isovist_to_cartesian_a(isovist3, 0, 0, 1.0)
-    polygon = Polygon(xy, True)
-    p = PatchCollection([polygon])
-    p.set_facecolor('none')
-    p.set_edgecolor('#000000')
-    p.set_linewidth(0.2)
-    ax.add_collection(p)
-
-    ax.scatter([x[0] for x in locs], [x[1] for x in locs], c='k', s=8, marker='+')
-
-    annotation = ['x1', 'x2', 'y']
-    for i, anno in enumerate(annotation):
-        ax.annotate(anno, (locs[i][0]+0.1, locs[i][1]), size=8)
-
-    # style
-    ax.set_aspect('equal')
-    lim = 1.5
-    ax.set_xlim(-lim,lim)
-    ax.set_ylim(-lim,lim)
-    ax.set_xticks([])
-    ax.set_yticks([])
-    ax.axis('off')
-
-    # for plot with torchvision util
-    fig.canvas.draw()
-    data = np.frombuffer(fig.canvas.tostring_rgb(), dtype=np.uint8)
-    w, h = fig.canvas.get_width_height()
-    im = data.reshape((int(h), int(w), -1))
-    im = im.transpose((2, 0, 1))
-    plt.close()
-    return im
-
-# showing isovist sequence
-def seq_show(locs, isovists, figsize=(8, 8)):
-    # walk trough the sequence
-    p_loc = np.array((0, 0))
-    b_segments = []
-    b_points = []
-    isovists_pts = []
-    res = np.pi/128
-    p_loc = np.array([0,0])
-    cartesian_locs = []
-    for loc, isovist in zip(locs, isovists):
-        rel_pos = np.asarray(pol2car(loc[0], loc[1]*2*np.pi, p_loc[0], p_loc[1]))
-        for j, rho in enumerate(isovist):
-            if rho < 0.98 :
-                pt = pol2car(rho, j*res, rel_pos[0], rel_pos[1])
-                b_points.append(pt)
-        segments = isovist_to_cartesian_segment_a(isovist, rel_pos[0], rel_pos[1], 1.0)
-        b_segments.extend(segments)
-        isovists_pts.append(isovist_to_cartesian_a(isovist, rel_pos[0], rel_pos[1], 1.0))
-        cartesian_locs.append(rel_pos)
-        p_loc = rel_pos
-
-    fig, ax = plt.subplots(1,1, figsize=figsize, dpi=96)
-
-    
-    # isovists
-    isovist_poly = []
-    for isovist_pts in isovists_pts:
-        isovist_poly.append(Polygon(isovist_pts, True))
-    r = PatchCollection(isovist_poly)
-    r.set_facecolor('#000000')
-    r.set_edgecolor(None)
-    r.set_alpha(0.02)
-    ax.add_collection(r)
-    
-
-    # isovist path
-    q = PatchCollection([Polygon(cartesian_locs, False)])
-    q.set_facecolor('none')
-    q.set_edgecolor('#cccccc')
-    q.set_linewidth(1.0)
-    q.set_linestyle('dashed')
-    ax.add_collection(q)
-    ax.scatter([x[0] for x in cartesian_locs], [x[1] for x in cartesian_locs], s = 6.0, c='red')
-
-    # boundaries
-    edge_patches = []
-    for segment in b_segments:
-        polygon = Polygon(segment, False)
-        edge_patches.append(polygon)
-    p = PatchCollection(edge_patches)
-    p.set_facecolor('none')
-    p.set_edgecolor('#000000')
-    p.set_linewidth(1.0)
-    ax.add_collection(p)
-    ax.scatter([x[0] for x in b_points], [x[1] for x in b_points], s = 0.05, c='k')
-
-
-    # style
-    ax.set_aspect('equal')
-    lim = 1.5
-    ax.set_xlim(-lim,lim)
-    ax.set_ylim(-lim,lim)
-    ax.set_xticks([])
-    ax.set_yticks([])
-    ax.axis('off')
-
-    return fig
-
-
-# plotting isovist sequence
-def plot_isovist_sequence(locs, isovists, figsize=(8,8)):
-    fig = seq_show(locs, isovists, figsize=figsize)
-
-    # for plot with torchvision util
-    fig.canvas.draw()
-    data = np.frombuffer(fig.canvas.tostring_rgb(), dtype=np.uint8)
-    w, h = fig.canvas.get_width_height()
-    im = data.reshape((int(h), int(w), -1))
-    im = im.transpose((2, 0, 1))
-    plt.close()
-    return im
-
-
 def index_to_loc_grid(idx, d):
     if idx == 0:
         return np.array((0., 0.), dtype=np.float32)

utils/misc.py

@@ -1,56 +1,14 @@
 import json
-from os.path import join
 import numpy as np
-from PIL import Image
 from utils.isoutil import *
-import torch
-import torchvision
 import sys
 
 
-class MeanTracker(object):
-    def __init__(self, name):
-        self.values = []
-        self.name = name
-
-    def add(self, val):
-        self.values.append(float(val))
-
-    def mean(self):
-        return np.mean(self.values)
-
-    def flush(self):
-        mean = self.mean()
-        self.values = []
-        return self.name, mean
-
-def save_params(config, training_path):
-    save_dict_path = join(training_path, 'param.json')
-    with open(save_dict_path, 'w') as outfile:
-        json.dump(config,
-                   outfile,
-                   sort_keys=False,
-                   indent=4,
-                   separators=(',', ': '))
-
 def load_params(config_file):
     with open(config_file, 'r') as f:
         data = json.load(f)
     return data
 
-
-def save_images(isovists, iter_num, title, sample_folder):
-    figs=[]
-    for i, x_ in enumerate(isovists):
-        x_ = np.squeeze(x_)
-        figs.append(plot_isovist_numpy(x_, figsize=(1,1)))
-    figs = torch.tensor(figs, dtype=torch.float)
-    nrow = int(np.sqrt(isovists.shape[0]))
-    im = torchvision.utils.make_grid(figs, normalize=True, range=(0, 255), nrow=nrow)
-    im = Image.fromarray(np.uint8(np.transpose(im.numpy(), (1, 2, 0))*255))
-    im.save(join(sample_folder, f'{title}_{iter_num:06}.jpg'))
-
-
 def imshow(img):
     npimg = img.numpy()
     plt.figure(figsize = (30,30))