The invention discloses a crowd counting model based on deep learning and an implementation method thereof, and the method comprises the steps: S1, obtaining a crowd image, carrying out the preprocessing of the obtained crowd image, and generating a corresponding crowd density map through marking information; s2, zooming the input crowd image into a plurality of scale versions, extracting featuresof each scale through a plurality of sub-networks, and enhancing the features of each scale by using a feature enhancement module; s3, combining the features generated by the plurality of sub-networks to generate an estimated crowd density map; s4, calculating loss by utilizing the estimated crowd density map and the real crowd density map, and updating model parameters; and S5, iteratively carrying out the training process of the steps S1-S4 for multiple times by utilizing different crowd images until a stop condition is met.