The multimode fiber (MMF) has great potential to transmit high-resolution images with less invasive methods in endoscopy due to its large number of spatial modes and small core diameter. However, spatial modes crosstalk will inevitably occur in MMFs, which makes the received images become speckles. A conditional generative adversarial network (GAN) composed of a generator and a discriminator was utilized to reconstruct the received speckles. We conduct an MMF imaging experimental system of transmitting over 1 m MMF with a 50 μm core. Compared with the conventional method of U-net, this conditional GAN could reconstruct images with fewer training datasets to achieve the same performance and shows higher feature extraction capability.