Weird PIL behaviour

requirements.txt

numpy==1.19.1
opencv-python==4.3.0.36
Pillow==6.1.0
rope==0.17.0
scipy==1.3.0

Untitled.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "from PIL import Image\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAGQAAABkAQAAAABYmaj5AAAAH0lEQVR4nGNgQAH1/xHgAROK1ChvlDe4eKNgFAxVAAD2uwy11U7oWwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<PIL.Image.Image image mode=1 size=100x100 at 0x10A099310>"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "img = Image.new('1', (100, 100))\n",
    "img_pixels = img.load()\n",
    "\n",
    "for x in range(1, 99):\n",
    "    for y in range(1, 50):\n",
    "        img_pixels[x,y] = True\n",
    "        \n",
    "img"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<PIL.Image.Image image mode=1 size=100x100 at 0x10A12AD90>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ary = np.zeros((100,100), dtype=np.bool)\n",
    "\n",
    "for x in range(1, 99):\n",
    "    for y in range(1, 50):\n",
    "        ary[x,y] = True\n",
    "      \n",
    "Image.fromarray(ary)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<PIL.Image.Image image mode=1 size=100x100 at 0x10A138150>"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ary = np.zeros((100,100), dtype=np.bool)\n",
    "\n",
    "for x in range(1, 99):\n",
    "    for y in range(1, 50):\n",
    "        ary[y,x] = True # note that rows and columns are reversed\n",
    "      \n",
    "Image.fromarray(ary)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "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": "3.7.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}

Your code works for me without problems.

https://gist.github.com/furas/0210ce506e182dfd23c580290dbd382d