We spend about 90% of our time in indoor environments. These environments strongly influence our health, behavior, and psychological well-being, yet we know surprisingly little about how indoor characteristics shape our affective and approach-avoidance responses. This gap exists partly because previous studies relied on small, self-curated image sets created based on differing criteria, limiting generalizability and reproducibility. To address this, we introduce the Image Database for Everyday Affective Spaces (IDEAS), an open-access dataset of 1,800 high-quality, real-world photographs from the six most frequented indoor environments: offices, living rooms, dining rooms, kitchens, bedrooms, and restaurants. These images were rated by 900 participants on valence, tense arousal, energetic arousal, and approach-avoidance in two online studies. We examined the relationship between valence, tense arousal, and energetic arousal in our dataset using seven theoretical models. Our analyses revealed a strong negative correlation between valence and tense arousal ratings of indoor scenes, whereas valence and energetic arousal, as well as energetic arousal and tense arousal, were largely independent, providing support for the three-dimensional core affect model. Demographic variables had minimal influence on affective ratings, while participants showed high inter-rater reliability. IDEAS offers a valuable resource for advancing environmental preference and broader environmental psychology research, enabling more nuanced investigation of how specific indoor environments and their characteristics shape emotional experience. Beyond normative affective scores, the dataset includes a comprehensive set of low-, mid-, and high-level visual features, individual ratings, demographic data, and copyright information. The IDEAS dataset is available on the OSF (https://osf.io/g9ze5) and GitHub (https://github.com/FatihcDeniz/Image-Database-for-Everyday-Affective-Spaces).