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Framing is significant for the mobilization of social movements through shaping citizens’ interpretation of the problems they face, articulating solutions to the proposed problems, and providing the rationale to take collective actions. As modern information technologies facilitate images to become an increasingly dominant tool of framing nowadays, recent studies start to shift the focus from traditional text-based framing to visual framing. However, they are still limited to small-sample or qualitative analyses while a plethora of fine-grain traceable data has become accessible from social media. Using supervised machine learning methods, this paper analyzes over 50,000 images from Telegram, an instant messaging application, during the 2019 Hong Kong Anti-ELAB movement. It suggests that visual framing is significant to facilitate movement mobilization as images visualize and dramatize the brutality of police repression. On the other hand, this repression-centered framing concentrates the grievance of protesters on the Hong Kong Police, instead of the Hong Kong government, or the Chinese government.