File size: 13,824 Bytes
f3929e1
 
 
ea3cae7
f3929e1
ea3cae7
 
 
 
 
 
 
f3929e1
 
 
ea3cae7
 
 
f3929e1
ea3cae7
 
 
 
 
f3929e1
 
 
ea3cae7
f3929e1
 
ea3cae7
f3929e1
 
7204393
f3929e1
ea3cae7
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
f3929e1
ea3cae7
 
 
 
 
 
 
 
 
 
 
 
 
f3929e1
7204393
ea3cae7
7204393
ea3cae7
f3929e1
ea3cae7
f3929e1
 
7204393
ea3cae7
f3929e1
ea3cae7
 
 
 
 
 
 
 
 
f3929e1
ea3cae7
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
f3929e1
ea3cae7
 
7204393
ea3cae7
 
 
 
 
 
 
 
 
 
 
 
 
 
f3929e1
ea3cae7
7204393
ea3cae7
 
 
 
7204393
ea3cae7
 
7204393
ea3cae7
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
f3929e1
ea3cae7
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
import cv2
import numpy as np
import os
import gradio as gr
from PIL import Image
import tempfile

# Enable OpenCL for better performance if available
try:
    cv2.ocl.setUseOpenCL(True)
except:
    pass  # OpenCL might not be available in all environments

# ------------------- Black & White Converter Functions ------------------- #
def convert_to_black_white(image, threshold_value=127, method="otsu"):
    """Convert image to black and white using specified thresholding method"""
    if isinstance(image, str):
        image = cv2.imread(image)
    
    # Convert to grayscale if not already
    if len(image.shape) == 3:
        gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
    else:
        gray = image
    
    if method == "adaptive":
        binary = cv2.adaptiveThreshold(gray, 255, cv2.ADAPTIVE_THRESH_GAUSSIAN_C,
                                      cv2.THRESH_BINARY, 11, 2)
    elif method == "otsu":
        _, binary = cv2.threshold(gray, 0, 255, cv2.THRESH_BINARY + cv2.THRESH_OTSU)
    else:
        _, binary = cv2.threshold(gray, threshold_value, 255, cv2.THRESH_BINARY)
    
    return binary

def process_image_bw(image, threshold_method, threshold_value):
    """Process image with black and white thresholding for Gradio"""
    if image is None:
        raise gr.Error("No image provided")
    
    if threshold_method != "manual":
        threshold_value = 0  # Not used for adaptive or Otsu
    
    # Convert to numpy array if PIL Image
    if isinstance(image, Image.Image):
        image_np = np.array(image)
        # Convert RGB to BGR for OpenCV
        if len(image_np.shape) == 3:
            image_np = cv2.cvtColor(image_np, cv2.COLOR_RGB2BGR)
    else:
        image_np = image
        
    result = convert_to_black_white(image_np, threshold_value, threshold_method)
    return Image.fromarray(result)

def process_video_bw(video_path, threshold_method, threshold_value):
    """Process video with black and white filter for Gradio"""
    if video_path is None:
        raise gr.Error("No video provided")
    
    if threshold_method != "manual":
        threshold_value = 0  # Not used for adaptive or Otsu
    
    try:
        cap = cv2.VideoCapture(video_path)
        if not cap.isOpened():
            raise gr.Error("Could not open video file")

        # Get video properties
        fourcc = cv2.VideoWriter_fourcc(*'mp4v')
        frame_width = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH))
        frame_height = int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT))
        fps = int(cap.get(cv2.CAP_PROP_FPS))
        
        # Create temporary output file
        temp_output = tempfile.NamedTemporaryFile(suffix='.mp4', delete=False)
        output_path = temp_output.name
        temp_output.close()
        
        # Create video writer
        out = cv2.VideoWriter(output_path, fourcc, fps, (frame_width, frame_height), isColor=False)
        
        # Process each frame
        while cap.isOpened():
            ret, frame = cap.read()
            if not ret:
                break
                
            bw_frame = convert_to_black_white(frame, threshold_value, threshold_method)
            out.write(bw_frame)
            
        cap.release()
        out.release()
        
        return output_path
    except Exception as e:
        raise gr.Error(f"Error processing video: {str(e)}")

# ------------------- Pencil Sketch Converter Functions ------------------- #
def process_image_sketch(image, intensity, blur_ksize, sigma):
    """Process image with pencil sketch effect for Gradio"""
    if image is None:
        raise gr.Error("No image provided")
    
    # Convert to numpy array if PIL Image
    if isinstance(image, Image.Image):
        image_np = np.array(image)
        # Convert RGB to BGR for OpenCV
        if len(image_np.shape) == 3:
            image_np = cv2.cvtColor(image_np, cv2.COLOR_RGB2BGR)
    else:
        image_np = image
    
    # Convert to grayscale
    gray = cv2.cvtColor(image_np, cv2.COLOR_BGR2GRAY) if len(image_np.shape) == 3 else image_np
    
    # Create sketch effect
    inverted = cv2.bitwise_not(gray)
    blur_ksize = blur_ksize if blur_ksize % 2 == 1 else blur_ksize + 1  # Ensure kernel size is odd
    blurred = cv2.GaussianBlur(inverted, (blur_ksize, blur_ksize), sigma)
    sketch = cv2.divide(gray, cv2.bitwise_not(blurred), scale=intensity)
    
    return Image.fromarray(sketch)

def process_video_sketch(video_path, intensity, blur_ksize, sigma):
    """Process video with pencil sketch effect for Gradio"""
    if video_path is None:
        raise gr.Error("No video provided")
    
    try:
        cap = cv2.VideoCapture(video_path)
        if not cap.isOpened():
            raise gr.Error("Could not open video file")

        # Get video properties
        fourcc = cv2.VideoWriter_fourcc(*'mp4v')
        frame_width = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH))
        frame_height = int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT))
        fps = int(cap.get(cv2.CAP_PROP_FPS))
        
        # Create temporary output file
        temp_output = tempfile.NamedTemporaryFile(suffix='.mp4', delete=False)
        output_path = temp_output.name
        temp_output.close()
        
        # Create video writer
        out = cv2.VideoWriter(output_path, fourcc, fps, (frame_width, frame_height), isColor=True)
        
        # Process each frame
        while cap.isOpened():
            ret, frame = cap.read()
            if not ret:
                break
                
            gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
            inverted = cv2.bitwise_not(gray)
            blur_ksize_adj = blur_ksize if blur_ksize % 2 == 1 else blur_ksize + 1
            blurred = cv2.GaussianBlur(inverted, (blur_ksize_adj, blur_ksize_adj), sigma)
            sketch = cv2.divide(gray, cv2.bitwise_not(blurred), scale=intensity)
            sketch_bgr = cv2.cvtColor(sketch, cv2.COLOR_GRAY2BGR)
            out.write(sketch_bgr)
            
        cap.release()
        out.release()
        
        return output_path
    except Exception as e:
        raise gr.Error(f"Error processing video: {str(e)}")

# ------------------- Create Gradio Interface ------------------- #
def update_blur(value):
    """Ensure blur kernel size is always odd"""
    return value if value % 2 == 1 else value + 1

def create_interface():
    # App title and description
    title = "Image & Video Processor"
    description = """
    # Image and Video Processing App
    
    This app provides tools to convert images and videos to black & white or pencil sketch styles.
    
    ## Features:
    - **Black & White Conversion**: Apply different thresholding methods
    - **Pencil Sketch Effect**: Create artistic pencil drawings with customizable parameters
    - **Support for both images and videos**
    
    Made with ❤️ using Gradio and OpenCV
    """
    
    # Black and White Image Interface
    with gr.Blocks(title=title) as app:
        gr.Markdown(description)
        
        with gr.Tab("Black & White Converter"):
            with gr.Tab("Image"):
                with gr.Row():
                    with gr.Column():
                        bw_image_input = gr.Image(label="Input Image", type="numpy")
                        bw_method = gr.Radio(
                            choices=["otsu", "adaptive", "manual"],
                            value="otsu",
                            label="Thresholding Method"
                        )
                        bw_threshold = gr.Slider(
                            minimum=0,
                            maximum=255,
                            value=127,
                            step=1,
                            label="Manual Threshold (0-255)",
                            interactive=True
                        )
                        bw_image_btn = gr.Button("Convert to Black & White")
                    
                    with gr.Column():
                        bw_image_output = gr.Image(label="Processed Image")
                
                # Show/hide threshold slider based on method
                def update_threshold_visibility(method):
                    return gr.update(visible=(method == "manual"))
                
                bw_method.change(fn=update_threshold_visibility, inputs=bw_method, outputs=bw_threshold)
            
            with gr.Tab("Video"):
                with gr.Row():
                    with gr.Column():
                        bw_video_input = gr.Video(label="Input Video")
                        bw_video_method = gr.Radio(
                            choices=["otsu", "adaptive", "manual"],
                            value="otsu",
                            label="Thresholding Method"
                        )
                        bw_video_threshold = gr.Slider(
                            minimum=0,
                            maximum=255,
                            value=127,
                            step=1,
                            label="Manual Threshold (0-255)",
                            interactive=True
                        )
                        bw_video_btn = gr.Button("Convert to Black & White")
                    
                    with gr.Column():
                        bw_video_output = gr.Video(label="Processed Video")
                
                # Show/hide threshold slider based on method
                bw_video_method.change(fn=update_threshold_visibility, inputs=bw_video_method, outputs=bw_video_threshold)
        
        with gr.Tab("Pencil Sketch Converter"):
            with gr.Tab("Image"):
                with gr.Row():
                    with gr.Column():
                        sketch_image_input = gr.Image(label="Input Image", type="numpy")
                        sketch_intensity = gr.Slider(
                            minimum=1,
                            maximum=255,
                            value=255,
                            step=1,
                            label="Intensity (1-255)"
                        )
                        sketch_blur = gr.Slider(
                            minimum=1,
                            maximum=99,
                            value=21,
                            step=2,
                            label="Blur Kernel Size (odd, 1-99)"
                        )
                        sketch_sigma = gr.Slider(
                            minimum=0,
                            maximum=50,
                            value=0,
                            step=0.1,
                            label="Standard Deviation (0-50)"
                        )
                        sketch_image_btn = gr.Button("Convert to Pencil Sketch")
                    
                    with gr.Column():
                        sketch_image_output = gr.Image(label="Processed Image")
            
            with gr.Tab("Video"):
                with gr.Row():
                    with gr.Column():
                        sketch_video_input = gr.Video(label="Input Video")
                        sketch_video_intensity = gr.Slider(
                            minimum=1,
                            maximum=255,
                            value=255,
                            step=1,
                            label="Intensity (1-255)"
                        )
                        sketch_video_blur = gr.Slider(
                            minimum=1,
                            maximum=99,
                            value=21,
                            step=2,
                            label="Blur Kernel Size (odd, 1-99)"
                        )
                        sketch_video_sigma = gr.Slider(
                            minimum=0,
                            maximum=50,
                            value=0,
                            step=0.1,
                            label="Standard Deviation (0-50)"
                        )
                        sketch_video_btn = gr.Button("Convert to Pencil Sketch")
                    
                    with gr.Column():
                        sketch_video_output = gr.Video(label="Processed Video")
        
        # Examples section
        with gr.Accordion("Examples", open=False):
            gr.Markdown("""
            ## Example Usage:
            
            1. **Black & White Conversion**: Great for document scanning, text enhancement, or artistic effects
            2. **Pencil Sketch**: Perfect for creating artistic renderings from photos
            
            Try uploading your own images or videos!
            """)
        
        # Set up event listeners
        bw_image_btn.click(
            fn=process_image_bw,
            inputs=[bw_image_input, bw_method, bw_threshold],
            outputs=bw_image_output
        )
        
        bw_video_btn.click(
            fn=process_video_bw,
            inputs=[bw_video_input, bw_video_method, bw_video_threshold],
            outputs=bw_video_output
        )
        
        sketch_image_btn.click(
            fn=process_image_sketch,
            inputs=[sketch_image_input, sketch_intensity, sketch_blur, sketch_sigma],
            outputs=sketch_image_output
        )
        
        sketch_video_btn.click(
            fn=process_video_sketch,
            inputs=[sketch_video_input, sketch_video_intensity, sketch_video_blur, sketch_video_sigma],
            outputs=sketch_video_output
        )
        
        # Make blur slider always odd
        sketch_blur.change(update_blur, sketch_blur, sketch_blur)
        sketch_video_blur.change(update_blur, sketch_video_blur, sketch_video_blur)
        
    return app

# Create and launch the app
app = create_interface()

# This is needed for Hugging Face Spaces
if __name__ == "__main__":
    app.launch()