added image watermark remover

app.py

@@ -2,6 +2,7 @@ import gradio as gr
 from video_watermark_remover import *
 from video_convertor import *
 from image_convertor import *
+from image_watermark_remover import *
 
 css = """
     #remove_btn {
@@ -29,6 +30,44 @@ css = """
 
 demo = gr.Blocks(css=css, title="Video Watermark Remover")
 with demo:
+    with gr.Tab("Image Convertor"):
+        gr.Markdown("""
+        # <center>🖼️ Image Convertor</center>
+        """)
+        image_format = ['jpg', 'jpeg', 'png', 'bmp', 'tiff', 'gif', 'webp', 'ico', 'heic', 'heiv', 'heif']
+        with gr.Row():
+            with gr.Column():
+                input_image = gr.File(label="Upload an Image")
+            with gr.Column():
+                with gr.Row():
+                    with gr.Row():
+                        image_format = gr.Radio(image_format, label="Select Format", interactive=False)
+                    with gr.Row():
+                        image_convert_btn = gr.Button("Convert Image", interactive=False, elem_id="convert_btn")
+        with gr.Row():
+            output_image = gr.File(label="Output File", interactive=False)
+        image_status = gr.Textbox(label="Status", interactive=False)
+        input_image.change(lambda x: gr.Radio.update(interactive=True), inputs=[input_image], outputs=[image_format])
+        image_format.change(lambda x: gr.Button.update(interactive=True), None, outputs=[image_convert_btn])
+        image_convert_btn.click(convert_image, inputs=[input_image, image_format], outputs=[output_image, image_status])
+
+    with gr.Tab("Image Watermark Remover"):
+        gr.Markdown("""
+        # <center>🖼️ Image Watermark Remover</center>
+        """)
+        with gr.Row():
+            with gr.Column():
+                input_image_watermark = gr.Image(label="Upload an Image", tool="sketch", type="pil", interactive=True)
+            with gr.Row():
+                with gr.Column():
+                    pass
+                with gr.Column():
+                    image_remove_btn = gr.Button("Remove Watermark", interactive=False, elem_id="remove_btn")
+                with gr.Column():
+                    pass
+        output_image_clean = gr.Image(label="Output Image", interactive=True)
+        image_remove_btn.click(remove_image_watermark, inputs=[input_image_watermark], outputs=[output_image_clean])
+
     with gr.Tab("Video Watermark Remover"):
         gr.Markdown("""
         # <center>🎥 Video Watermark Remover (Slow)</center>
@@ -78,26 +117,7 @@ with demo:
         format.change(lambda x: gr.Button.update(interactive=True), None, outputs=[convert_btn])
         convert_btn.click(convert_video, inputs=[input_video, format], outputs=[output, status])
 
-    with gr.Tab("Image Convertor"):
-        gr.Markdown("""
-        # <center>🖼️ Image Convertor</center>
-        """)
-        image_format = ['jpg', 'jpeg', 'png', 'bmp', 'tiff', 'gif', 'webp', 'ico', 'heic', 'heiv', 'heif']
-        with gr.Row():
-            with gr.Column():
-                input_image = gr.File(label="Upload an Image")
-            with gr.Column():
-                with gr.Row():
-                    with gr.Row():
-                        image_format = gr.Radio(image_format, label="Select Format", interactive=False)
-                    with gr.Row():
-                        image_convert_btn = gr.Button("Convert Image", interactive=False, elem_id="convert_btn")
-        with gr.Row():
-            output_image = gr.File(label="Output File", interactive=False)
-        image_status = gr.Textbox(label="Status", interactive=False)
-        input_image.change(lambda x: gr.Radio.update(interactive=True), inputs=[input_image], outputs=[image_format])
-        image_format.change(lambda x: gr.Button.update(interactive=True), None, outputs=[image_convert_btn])
-        image_convert_btn.click(convert_image, inputs=[input_image, image_format], outputs=[output_image, image_status])
+    
     gr.Markdown("""## <center style="margin:20px;">Developed by Muhammad Ahmed<img src="https://avatars.githubusercontent.com/u/63394104?v=4" style="height:50px;width:50px;border-radius:50%;margin:5px;"></img></center>
     """)
 demo.launch(show_api=False)

image_watermark_remover.py

@@ -0,0 +1,61 @@
+import io
+import requests
+from PIL import Image
+
+def remove_image_watermark(input):
+    image = input["image"]
+    mask = input["mask"]
+    image_data = io.BytesIO()
+    image.save(image_data, format=image.format)
+    image_data = image_data.getvalue()
+
+    mask_data = io.BytesIO()
+    mask.save(mask_data, format=mask.format)
+    mask_data = mask_data.getvalue()
+
+    # Prepare form data
+    form_data = {
+            'ldmSteps': 25,
+            'ldmSampler': 'plms',
+            'zitsWireframe': True,
+            'hdStrategy': 'Original',
+            'hdStrategyCropMargin': 196,
+            'hdStrategyCropTrigerSize': 1280,
+            'hdStrategyResizeLimit': 2048,
+            'prompt': '',
+            'negativePrompt': '',
+            'croperX': -24,
+            'croperY': -23,
+            'croperHeight': 512,
+            'croperWidth': 512,
+            'useCroper': False,
+            'sdMaskBlur': 5,
+            'sdStrength': 0.75,
+            'sdSteps': 50,
+            'sdGuidanceScale': 7.5,
+            'sdSampler': 'pndm',
+            'sdSeed': 42,
+            'sdMatchHistograms': False,
+            'sdScale': 1,
+            'cv2Radius': 5,
+            'cv2Flag': 'INPAINT_NS',
+            'paintByExampleSteps': 50,
+            'paintByExampleGuidanceScale': 7.5,
+            'paintByExampleSeed': 42,
+            'paintByExampleMaskBlur': 5,
+            'paintByExampleMatchHistograms': False,
+            'sizeLimit': 1024,
+        }
+
+    files_data = {
+        'image': ('image.png', image_data),
+        'mask': ('mask.png', mask_data)
+    }
+
+    response = requests.post('https://ahmedghani-lama-cleaner-lama.hf.space/inpaint', data=form_data, files=files_data)
+
+    if response.headers['Content-Type'] == 'image/jpeg' or response.headers['Content-Type'] == 'image/png':
+        image = Image.open(io.BytesIO(response.content))
+        return image
+    else:
+        print(f"Error processing Image: {response.text}")